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A bouquet of lilies and tulips has 12 flowers. Lilies are 3$ each and tulips are 2$ each. The total cost is 32$. Write & Solve a system of linear equations to find the number of lilies and tulips in this bouquet.
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Chamberlain College of Nursing Chapter 8 Week 7 Confidence Intervals Essay
This is a two part paper. Course Project Part I
Required ResourcesRead/review the following resources for this activity: ...
Chamberlain College of Nursing Chapter 8 Week 7 Confidence Intervals Essay
This is a two part paper. Course Project Part I
Required ResourcesRead/review the following resources for this activity:
Textbook: Chapter 8
Lesson
Scenario/SummaryYou will complete a Course Project in this course that will span two
weeks. The final project is due the Sunday of Week 7. The project is
broken into two parts and it would be most effective to complete Part I
in Week 6 and Part II in Week 7. In Week 6, Confidence Intervals will be explored and in Week 7 Hypothesis testing will be explored.A confidence interval is a defined range of values such that there is
a specified probability that the value of a parameter lies within the
interval.In Part I of this project, you will pick a topic, complete research and provide a write-up that includes calculations. Round all values to two decimal places when appropriate.DeliverablesChoose a Topic where you can gather at least 50 pieces of data. Examples of Topics
The Golden Gate Warriors Points Per Game in 2016 (use the points scored in the first 50 games).
High School Graduation Rates by State (use the graduation rates for all 50 states)
Average Tuition Rates in the US (You have to find the tuition rates of 50 college/universities).
The prices of a hotel room per night in a major city (You have to find the price of the same night of hotels in one city).
Weights of 50 babies at birth.
Write at least a 1-Page ReportOpen a Word Document
Introduction--Provide a description of your topic and cite where you found your data.
Sample Data—Include a 5x10 table including your 50 values in your report. You must provide ALL of your sample data.
Problem Computations—For the topic you chose, you must answer the following:
Determine the mean and standard deviation of your sample.
Find the 80%, 95%, and 99% confidence intervals.
Make sure to list the margin of error for the 80%, 95%, and 99% confidence interval.
Create your own confidence interval (you cannot use 80%, 95%, and
99%) and make sure to show your work. Make sure to list the margin of
error.
Problem Analysis—Write a half-page reflection.
What trend do you see takes place to the confidence interval as the
confidence level rises? Explain mathematically why that takes place.
Provide a sentence for each confidence interval created in part c)
which explains what the confidence interval means in context of topic of
your project.
Explain how Part I of the project has helped you understand confidence intervals better?
How did this project help you understand statistics better?
Required SoftwareMicrosoft Office: Word and ExcelUse a personal copy or access the software at https://application.chamberlain.edu (Links to an external site.).GradingThis activity will be graded based on the Course Project grading rubric. You can view the rubric below.Course Project Rubric
Criteria
Ratings
Pts
Part I: Topic & Introduction
4.0 pts
3.0 ptsAbove Average Student picks appropriate topic and introduces data. No citation.
2.0 ptsAverage. Student does not pick a topic that is appropriate for the project, introduces the data but does not cite source.
1.0 ptsNeeds Improvement Students provides topic without descritption and citation.
0.0 ptsNo Effort. No topic, descritpion or citation is provided.
4.0 pts
Part I: Sample Data
4.0 ptsProficient Student provides ALL 50 pieces of data.
3.0 ptsAbove Average Student provides 30-49 pieces of data.
2.0 ptsAverage Student provides 20 - 29 pieces of data.
1.0 ptsNeeds Improvement Student provides 1-19 pieces of data.
0.0 ptsNo Effort. No Data was provided.
4.0 pts
Part I: Mean & Standard Deviation
5.0 ptsProficient Mean & Sample Standard Deviation of the data set is correct with no rounding error. .
4.0 ptsAbove Average Mean & Sample Standard Deviation of the data set is correct but with roujnding error.
3.0 ptsAverage One Value (either mean or sample standsrd deviation) is correct but the other is not correct.
1.0 ptsNeeds Improvement Both the Mean & Sample Standard Deviation are incorrect but it was attempted.
0.0 ptsNo Effort. The mean and sample standard deviation
5.0 pts
Part I: Constructing the 80%, 95%, 99% Confidence Intervals
15.0 ptsProficient Computes the 80%, 95%, and 99% confidence intervals correclty making sure to note the margin of error for each.
12.0 ptsAbove Average Computes the
80%, 95%, and 99% confidence intervals correclty but is missing margin
of errors (or some of the margin of errors are incorrect).
10.0 ptsAverage Computes the 80%, 95%, and 99% confidence intervals but there are some errors in the calculations.
6.0 ptsNeeds Improvement Computes
the 80%, 95%, and 99% confidence intervals but all of the values are
incorrect. The component was attempted.
0.0 ptsNo Effort. No Confidence Intervals are provided.
15.0 pts
Part I: Creating a new confidence interval
7.0 ptsProficient. Student computes a confidence interval (not 80%, 95%, 99%) correctly making sure to list the margin of error.
5.0 ptsAbove Average. Student
computes a confidence interval (not 80%, 95%, 99%) correctly making sure
to list the margin of error but there is rounding error.
4.0 ptsAverage. Student computes a confidence interval (not 80%, 95%, 99%) correctly but does not highlight the margin of error.
3.0 ptsNeeds Improvement Student computes a confidence interval (not 80%, 95%, 99%) but it was not done correctly.
0.0 ptsNo Effort. The student did not create a new confidence interval.
7.0 pts
Part I: Problem Analysis
10.0 ptsProficient. Student
addresses trend that takes place when the confidence level rises.
Provides a sentence for each confidence interval created explaining what
the confidence interval means in context of the data collected.
Provides a reflection for Part I of the project.
8.0 ptsAbove Average. Student
addresses trend that takes place when the confidence level rises.
Provides sentences for each confidence interval created explaining what
the confience interval means in context of the data collected. Does NOT
provide a Reflection.
7.0 ptsAverage. Student may or may
not address the trend that takes place when the confidence level rises.
Provides a sentence for SOME confidence intervaSl created explaining
what the confidence interval means in context of the data collected. A
reflection Part I of the project may or may not be provided.
5.0 ptsNeeds Improvement. Majority of the analysis is missing.
0.0 ptsNo Effort. No Problem Anaylsis is provided.
10.0 pts
Part II: Choose a Data Set & Preliminary Data
5.0 ptsProficient. Student computes all 4 Preliminary Data Values.
4.0 ptsAbove Average. Student computes all 3 Preliminary Data Values.
3.0 ptsAverage. Student computes all 2 Preliminary Data Values.
1.0 ptsNeeds Improvement. Student computes all 1 Preliminary Data Values.
0.0 ptsNo Effort. No Preliminary Data
5.0 pts
Part II: Hypothesis Testing
20.0 ptsProficient. Completes 4
Hypothesis Tests highlighting the null/alternate hypothesis, value of
test statistic, and report p-value.
16.0 ptsAbove Average. Completes 3
Hypothesis Tests highlighting the null/alternate hypothesis, value of
test statistic, and report p-value.
14.0 ptsAverage. Completes 2 Hypothesis Tests highlighting the null/alternate hypothesis, value of test statistic, and report p-value.
10.0 ptsNeeds Improvement: Completes
1 Hypothesis Test highlighting the null/alternate hypothesis, value of
test statistic, and report p-value.
0.0 ptsNo Effort. No Hypothesis Tests were completed.
20.0 pts
Part II: Hypothesis Testing Analysis
10.0 ptsProficient. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for ALL 4 Problems.
8.0 ptsAbove Average. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for 3 Problems.
7.0 ptsAverage. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for 2 Problems.
5.0 ptsNeeds Improvement. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for 1 Problem
0.0 ptsNo Effort. No conclusion/explanations were given.
10.0 pts
Part II: Proposal and computations for new hypothesis test
10.0 ptsProficient. Student creates
an original Hypothesis Test based on one of the data sets highlighting
the null/alternate hypothesis, value of test statistic, report p-value,
conclusion and explanation.
8.0 ptsProficient. Student creates
an original Hypothesis Test based on one of the data sets correclty and
has MOST of the content: highlighting the null/alternate hypothesis,
value of test statistic, report p-value, conclusion and explanation.
7.0 ptsAverage. Student creates an
original Hypothesis Test based on one of the data sets and MISSING MOST
of the content: highlighting the null/alternate hypothesis, value of
test statistic, report p-value, conclusion and explanation.
5.0 ptsNeeds Improvement. Student
creates an original Hypothesis Test based on one of the data sets but
there are multiple mistakes and/or conclusions are not valid.
0.0 ptsNo Effort. The student did not propose/compute a new hypothesis test.
10.0 pts
Total Points: 90.0
MA141 Grantham Week 5 Expected Value and Probability Paper
I need help with these questions. Also if a possible an explanation for each would be great to.
MA141 Grantham Week 5 Expected Value and Probability Paper
I need help with these questions. Also if a possible an explanation for each would be great to.
URGENT: mystatlab homework
i have 5 assignments left on mystatlab homework that is due tomorrow at 11:59. I've been scoring in the 90s on most of the ...
URGENT: mystatlab homework
i have 5 assignments left on mystatlab homework that is due tomorrow at 11:59. I've been scoring in the 90s on most of them but i am burnt and work all day tomorrow. Can someone help me?
AU Diabetic Medicare Enrollees Aged 65 to 75 Having Hemoglobin A1c Report
Assignment #1: Quantitative Analysis For
this assignment, students should choose data from the quantitative
analysis bel ...
AU Diabetic Medicare Enrollees Aged 65 to 75 Having Hemoglobin A1c Report
Assignment #1: Quantitative Analysis For
this assignment, students should choose data from the quantitative
analysis below and are asked to analyze it using Excel, RStuido (BONUS
points)Data set:Minnesota Healthcare Database.xlsxMedicare National Data by CountyMN Hospital Report Data by Care Unit FY2013MN HCCIS Imaging Procedures 2013MEPS Dental FilesMEPS Inpatient Stay DatabaseStudents
will develop an analysis report, in five main sections, including
introduction, research method (research questions/objective, data set,
research method, and analysis), results, conclusion and health policy
recommendations. This is a 5-6 page individual project report.Here are the main steps for this assignment.TOPIC: - Comparing average annual percent of diabetic Medicare enrollees age 65-75 having hemoglobin A1c between B and W (#1)Step 2: Develop the research question andStep 3: Run the analysis using EXCEL (RStudio for BONUS points) and report the findings using the assignment instruction.The Report Structure:Start with the1.Cover page (1 page, including running head).Please look at the example http://www.apastyle.org/manual/related/sample-experiment-paper-1.pdf (you can download the file from the class) and http://www.umgc.edu/library/libhow/apa_tutorial.cfm to learn more about the APA style.In the title page include:Title, this is the approved topic by your instructor.Student nameClass nameInstructor nameDate2.IntroductionIntroduce the problem or topic being investigated. Include relevant background information, for example; Indicates why this is an issue or topic worth researching;Highlight how others have researched this topic or issue (whether quantitatively or qualitatively), andSpecify how others have operationalized this concept and measured these phenomenaNote: Introduction should not be more than one or two paragraphs.Literature ReviewThere is no need for a literature review in this assignment3.Research Question or Research HypothesisWhat is the Research Question or Research Hypothesis?***Just in time information: Here are a few points for Research Question or Research HypothesisThere
are basically two kinds of research questions: testable and
non-testable. Neither is better than the other, and both have a place in
applied research.Examples of non-testable questions are:How do managers feel about the reorganization?What do residents feel are the most important problems facing the community?Respondents'
answers to these questions could be summarized in descriptive tables
and the results might be extremely valuable to administrators and
planners. Business and social science researchers often ask non-testable
research questions. The shortcoming with these types of questions is
that they do not provide objective cut-off points for decision-makers.In
order to overcome this problem, researchers often seek to answer one or
more testable research questions. Nearly all testable research
questions begin with one of the following two phrases:Is there a significant difference between ...?Is there a significant relationship between ...? For example:Is there a significant relationship between the age of managers? and their attitudes towards the reorganization?A
research hypothesis is a testable statement of opinion. It is created
from the research question by replacing the words "Is there" with the
words "There is," and also replacing the question mark with a period.
The hypotheses for the two sample research questions would be:There is a significant relationship between the age of managers and their attitudes towards the reorganization.
It is not possible to test a hypothesis directly. Instead, you must
turn the hypothesis into a null hypothesis. The null hypothesis is
created from the hypothesis by adding the words "no" or "not" to the
statement. For example, the null hypotheses for the two examples would
be:There is no significant relationship between the age of managersand their attitudes towards the reorganization.There is no significant difference between white and minority residentswith respect to what they feel are the most important problems facing the community.All
statistical testing is done on the null hypothesis...never the
hypothesis. The result of a statistical test will enable you to either:1) reject the null hypothesis, or2) fail to reject the null hypothesis. Never use the words "accept the null hypothesis." *Source:
StatPac for Windows Tutorial. (2017). User's Guide; Formulating
Hypotheses from Research Questions. Retrieved May 17, 2019 from https://statpac.com/manual/index.htm?turl=formulatinghypothesesfromresearchquestions.htmWhat does significance really mean?“Significance
is a statistical term that tells how sure you are that a difference or
relationship exists. To say that a significant difference or
relationship exists only tells half the story. We might be very sure
that a relationship exists, but is it a strong, moderate, or weak
relationship? After finding a significant relationship, it is important
to evaluate its strength. Significant relationships can be strong or
weak. Significant differences can be large or small. It just depends on
your sample size.To determine whether the observed difference is statistically significant, we look at two outputs of our statistical test:P-value:
The primary output of statistical tests is the p-value (probability
value). It indicates the probability of observing the difference if no
difference exists.The
p-value from above example, 0.9926, indicates that we DO NOT expect to
see a meaningless (random) difference of 5% or more in ‘hospital beds’
only about 993 times in 1000 there is no difference (0.9926*1000=992.6 ~
993).Note: This is an example from the week1 exercise.The
p-value from above example, 0.0001, indicates that we’d expect to see a
meaningless (random) ‘number of the employees on payer’ difference of
5% or more only about 0.1 times in 1000 (0.0001 * 1000=0.1). CI
around Difference: A confidence interval around a difference that does
not cross zero also indicates statistical significance. The graph below
shows the 95% confidence interval around the difference between hospital
beds in 2011 and 2012 (CI: [-40.82 ; 40.44]):CI around Difference: A confidence interval around a difference that does not cross zero also indicates statistical significance. The graph below shows the 95% confidence interval around the difference between hospital beds in 2011 and 2012 (CI: [-382.16 ; 125.53]):The
boundaries of this confidence interval around the difference also
provide a way to see what the upper [40.44] and lower bounds [-40.82].As a summary:“Statistically significant means a result is unlikely due to chance.The
p-value is the probability of obtaining the difference we saw from a
sample (or a larger one) if there really isn’t a difference for all
users.Statistical significance doesn’t mean practical
significance. Only by considering context can we determine whether a
difference is practically significant; that is, whether it requires
action.The confidence interval around the difference also
indicates statistical significance if the interval does not cross zero.
It also provides likely boundaries for any improvement to aide in
determining if a difference really is noteworthy.With large
sample sizes, you’re virtually certain to see statistically significant
results, in such situations, it’s important to interpret the size of the
difference”("Measuring U", 2019).*ResourceMeasuring U. (2019). Statistically significant. Retrieved May 17, 2019 from: https://measuringu.com/statistically-significant/Small
sample sizes often do not yield statistical significance; when they do,
the differences themselves tend also to be practically significant;
that is, meaningful enough to warrant action.4.Research MethodDiscuss
the Research Methodology (in general). Describe the variable or
variables that are being analyzed. Identify the statistical test you
will select to analyze these data and explain why you chose this test.
Summarize your statistical alternative hypothesis. This section includes
the following sub-sections:a)Describe the DatasetExample:
The primary source of data will be HOSPITAL COMPARE MEDICARE DATA
(citation). This dataset provides information on hospital
characteristics, such as: Number of staffed beds, ownership, system
membership, staffing by nurses and non-clinical staff, teaching status,
percentage of discharge for Medicare and Medicaid patients, and
information regarding the availability of specialty and high-tech
services, as well as Electronic Medical Record (EMR) use (Describe
dataset in 2-3 lines, Google the dataset and find the related website to
find more information about the data).Also, describe the sample
size; for example, “The writer is using Medicare data-2013, this data
includes 3000 obs. for all of the hospitals in the US.”b)Describe VariablesNext,
review the database you selected and select a variable or variables
that are a “best-fit.” That is, choose a variable that quantitatively
measures the concept or concepts articulated in your research question
or hypothesis. Return to your previously stated Research Question
or Hypothesis and evaluate it considering the variables you have
selected. (See the sample Table 1).Table 1. List of variables used for the analysisVariableDefinitionDescriptionof codeSourceYearTotal Hospital BedsTotal facility beds set up and staffedat the end of the reporting periodNumericMN Data2013….….. Source: UMGC, 2019 ***Just in time information:To cite a dataset, you can go with two approaches:First, look at the note in the dataset for example;Medicare National Data by County. (2012). Dartmouth Atlas of Health Care, A Second, use the online citation, for example:Zare,
H., (2019, May). MN Hospital Report Data. Data posted in University of
Maryland University College HMGT 400 online classroom, archived at: http://campus.umgc.eduSee two examples describing the variables from Minnesota Data:Table 2. Definition of variables used in the analysisVariableDefinitionDescriptionof codeSourceYearhospital_bedsTotal facility beds set up and staffedat the end of the reporting periodNumericMN data2013yearFYCategoricalMN data2013 Source: UMGC, 2019c)Describe the Research Method for AnalysisFirst,
describe the research method as a general (e.g., this is a quantitative
method and then explain about this method in about one paragraph. If
you have this part in the introduction, you do not need to add here).Then,
explain the statistical method you plan to use for your analysis (Refer
to content in week 3 on Biostatistics for information on various
statistical methods you can choose from).Example:Hypothesis: AZ hospitals are more likely to have lower readmission rates for PN compared to CA.Research
Method: To determine whether Arizona hospitals are more likely to have
lower readmission rate than California, we will use a t-test, to
determine whether differences across hospital types are statistically
significant (You can change the test depends on your analysis).d)Describe statistical packageAdd one paragraph for the statistical package, e.g., Excel or RStudio.5. ResultsDiscuss your findings considering the following tips:▪
Why you needed to see the distribution of data before any analysis
(e.g., check for outliers, finding the best fit test; for example, if
the data had not a normal distribution, you can’t use the parametric
test, etc., so just add 1 or 2 sentences).▪ Did you eliminate outliers? (Please write 1 or 2 sentences, if applicable).▪ How many observations do you have in your database and how many for selected variables, report % of missing.▪ When you are finished with this, go for the next steps:Present
the results of your statistical analysis; include any relevant
statistical information (summary tables, including N, mean, std. dev.).
Make sure to completely and correctly name all your columns and rows,
tables and variables. For this part you could have at least 1-2 tables
and 1-2 figures (depending on your variables bar-chart, pi-chart, or
scatter-plot), you can use a table like this:Table 3. Descriptive analysis to compare % of BL in Medicare beneficiary, MD vs. VA- 2013VariableObs.MeanSDP-valuePer of Lipid in MD2483.202.320.4064 Per of Lipid in VA 124 82.694.41 Source: UMGC, 2019When
you have tables and plots ready, think about your finding and state the
statistical conclusion. That is, do the results present evidence in
favor or the null hypothesis or evidence that contradicts the null
hypothesis?6.Conclusion and DiscussionReview your research questions or hypothesis. How
has your analysis informed this question or hypothesis? Present your
conclusion(s) from the results (presented above) and discuss the meaning
of this conclusion(s) considering the research question or hypothesis
presented in your introduction. At the end of this section, add
one or two sentences and discuss the limitations (including biases)
associated with this analysis and any other statements you think are
important in understanding the results of this analysis. ReferencesInclude
a reference page listing the bibliographic information for all sources
cited in this report. This information should be consistent with the
requirements specified in the American Psychological Association (APA)
format and style guide.
Use of Tessellations and The Type of Transformation Used and Why Paper
Create?a tessellation pattern using Microsoft®?Paint, GeoGebra, Microsoft®?PowerPoint®, or other means available to you ...
Use of Tessellations and The Type of Transformation Used and Why Paper
Create?a tessellation pattern using Microsoft®?Paint, GeoGebra, Microsoft®?PowerPoint®, or other means available to you and approved by the instructor; or you may draw something by hand. Refer to the following resources for help with creating a tessellation:
Tessellation Help
Drawing a Tessellation by Hand
Tessellation Example and Non-Example
Technology Resource Library
Use?color and shading to make your tessellation visually pleasing.
Write?a minimum 350-word?paper that includes the following:
An explanation of why you chose the tessellated figure
The type of transformation used and why
The actual tessellation or a picture of the created tessellation
Some real-world examples of tessellations that you can find
How you might use real-world examples of tessellations to help elementary-level students understand tessellations
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Chamberlain College of Nursing Chapter 8 Week 7 Confidence Intervals Essay
This is a two part paper. Course Project Part I
Required ResourcesRead/review the following resources for this activity: ...
Chamberlain College of Nursing Chapter 8 Week 7 Confidence Intervals Essay
This is a two part paper. Course Project Part I
Required ResourcesRead/review the following resources for this activity:
Textbook: Chapter 8
Lesson
Scenario/SummaryYou will complete a Course Project in this course that will span two
weeks. The final project is due the Sunday of Week 7. The project is
broken into two parts and it would be most effective to complete Part I
in Week 6 and Part II in Week 7. In Week 6, Confidence Intervals will be explored and in Week 7 Hypothesis testing will be explored.A confidence interval is a defined range of values such that there is
a specified probability that the value of a parameter lies within the
interval.In Part I of this project, you will pick a topic, complete research and provide a write-up that includes calculations. Round all values to two decimal places when appropriate.DeliverablesChoose a Topic where you can gather at least 50 pieces of data. Examples of Topics
The Golden Gate Warriors Points Per Game in 2016 (use the points scored in the first 50 games).
High School Graduation Rates by State (use the graduation rates for all 50 states)
Average Tuition Rates in the US (You have to find the tuition rates of 50 college/universities).
The prices of a hotel room per night in a major city (You have to find the price of the same night of hotels in one city).
Weights of 50 babies at birth.
Write at least a 1-Page ReportOpen a Word Document
Introduction--Provide a description of your topic and cite where you found your data.
Sample Data—Include a 5x10 table including your 50 values in your report. You must provide ALL of your sample data.
Problem Computations—For the topic you chose, you must answer the following:
Determine the mean and standard deviation of your sample.
Find the 80%, 95%, and 99% confidence intervals.
Make sure to list the margin of error for the 80%, 95%, and 99% confidence interval.
Create your own confidence interval (you cannot use 80%, 95%, and
99%) and make sure to show your work. Make sure to list the margin of
error.
Problem Analysis—Write a half-page reflection.
What trend do you see takes place to the confidence interval as the
confidence level rises? Explain mathematically why that takes place.
Provide a sentence for each confidence interval created in part c)
which explains what the confidence interval means in context of topic of
your project.
Explain how Part I of the project has helped you understand confidence intervals better?
How did this project help you understand statistics better?
Required SoftwareMicrosoft Office: Word and ExcelUse a personal copy or access the software at https://application.chamberlain.edu (Links to an external site.).GradingThis activity will be graded based on the Course Project grading rubric. You can view the rubric below.Course Project Rubric
Criteria
Ratings
Pts
Part I: Topic & Introduction
4.0 pts
3.0 ptsAbove Average Student picks appropriate topic and introduces data. No citation.
2.0 ptsAverage. Student does not pick a topic that is appropriate for the project, introduces the data but does not cite source.
1.0 ptsNeeds Improvement Students provides topic without descritption and citation.
0.0 ptsNo Effort. No topic, descritpion or citation is provided.
4.0 pts
Part I: Sample Data
4.0 ptsProficient Student provides ALL 50 pieces of data.
3.0 ptsAbove Average Student provides 30-49 pieces of data.
2.0 ptsAverage Student provides 20 - 29 pieces of data.
1.0 ptsNeeds Improvement Student provides 1-19 pieces of data.
0.0 ptsNo Effort. No Data was provided.
4.0 pts
Part I: Mean & Standard Deviation
5.0 ptsProficient Mean & Sample Standard Deviation of the data set is correct with no rounding error. .
4.0 ptsAbove Average Mean & Sample Standard Deviation of the data set is correct but with roujnding error.
3.0 ptsAverage One Value (either mean or sample standsrd deviation) is correct but the other is not correct.
1.0 ptsNeeds Improvement Both the Mean & Sample Standard Deviation are incorrect but it was attempted.
0.0 ptsNo Effort. The mean and sample standard deviation
5.0 pts
Part I: Constructing the 80%, 95%, 99% Confidence Intervals
15.0 ptsProficient Computes the 80%, 95%, and 99% confidence intervals correclty making sure to note the margin of error for each.
12.0 ptsAbove Average Computes the
80%, 95%, and 99% confidence intervals correclty but is missing margin
of errors (or some of the margin of errors are incorrect).
10.0 ptsAverage Computes the 80%, 95%, and 99% confidence intervals but there are some errors in the calculations.
6.0 ptsNeeds Improvement Computes
the 80%, 95%, and 99% confidence intervals but all of the values are
incorrect. The component was attempted.
0.0 ptsNo Effort. No Confidence Intervals are provided.
15.0 pts
Part I: Creating a new confidence interval
7.0 ptsProficient. Student computes a confidence interval (not 80%, 95%, 99%) correctly making sure to list the margin of error.
5.0 ptsAbove Average. Student
computes a confidence interval (not 80%, 95%, 99%) correctly making sure
to list the margin of error but there is rounding error.
4.0 ptsAverage. Student computes a confidence interval (not 80%, 95%, 99%) correctly but does not highlight the margin of error.
3.0 ptsNeeds Improvement Student computes a confidence interval (not 80%, 95%, 99%) but it was not done correctly.
0.0 ptsNo Effort. The student did not create a new confidence interval.
7.0 pts
Part I: Problem Analysis
10.0 ptsProficient. Student
addresses trend that takes place when the confidence level rises.
Provides a sentence for each confidence interval created explaining what
the confidence interval means in context of the data collected.
Provides a reflection for Part I of the project.
8.0 ptsAbove Average. Student
addresses trend that takes place when the confidence level rises.
Provides sentences for each confidence interval created explaining what
the confience interval means in context of the data collected. Does NOT
provide a Reflection.
7.0 ptsAverage. Student may or may
not address the trend that takes place when the confidence level rises.
Provides a sentence for SOME confidence intervaSl created explaining
what the confidence interval means in context of the data collected. A
reflection Part I of the project may or may not be provided.
5.0 ptsNeeds Improvement. Majority of the analysis is missing.
0.0 ptsNo Effort. No Problem Anaylsis is provided.
10.0 pts
Part II: Choose a Data Set & Preliminary Data
5.0 ptsProficient. Student computes all 4 Preliminary Data Values.
4.0 ptsAbove Average. Student computes all 3 Preliminary Data Values.
3.0 ptsAverage. Student computes all 2 Preliminary Data Values.
1.0 ptsNeeds Improvement. Student computes all 1 Preliminary Data Values.
0.0 ptsNo Effort. No Preliminary Data
5.0 pts
Part II: Hypothesis Testing
20.0 ptsProficient. Completes 4
Hypothesis Tests highlighting the null/alternate hypothesis, value of
test statistic, and report p-value.
16.0 ptsAbove Average. Completes 3
Hypothesis Tests highlighting the null/alternate hypothesis, value of
test statistic, and report p-value.
14.0 ptsAverage. Completes 2 Hypothesis Tests highlighting the null/alternate hypothesis, value of test statistic, and report p-value.
10.0 ptsNeeds Improvement: Completes
1 Hypothesis Test highlighting the null/alternate hypothesis, value of
test statistic, and report p-value.
0.0 ptsNo Effort. No Hypothesis Tests were completed.
20.0 pts
Part II: Hypothesis Testing Analysis
10.0 ptsProficient. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for ALL 4 Problems.
8.0 ptsAbove Average. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for 3 Problems.
7.0 ptsAverage. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for 2 Problems.
5.0 ptsNeeds Improvement. State correct conclusion (Reject/Fail to Reject) and valid explanations in context of the data for 1 Problem
0.0 ptsNo Effort. No conclusion/explanations were given.
10.0 pts
Part II: Proposal and computations for new hypothesis test
10.0 ptsProficient. Student creates
an original Hypothesis Test based on one of the data sets highlighting
the null/alternate hypothesis, value of test statistic, report p-value,
conclusion and explanation.
8.0 ptsProficient. Student creates
an original Hypothesis Test based on one of the data sets correclty and
has MOST of the content: highlighting the null/alternate hypothesis,
value of test statistic, report p-value, conclusion and explanation.
7.0 ptsAverage. Student creates an
original Hypothesis Test based on one of the data sets and MISSING MOST
of the content: highlighting the null/alternate hypothesis, value of
test statistic, report p-value, conclusion and explanation.
5.0 ptsNeeds Improvement. Student
creates an original Hypothesis Test based on one of the data sets but
there are multiple mistakes and/or conclusions are not valid.
0.0 ptsNo Effort. The student did not propose/compute a new hypothesis test.
10.0 pts
Total Points: 90.0
MA141 Grantham Week 5 Expected Value and Probability Paper
I need help with these questions. Also if a possible an explanation for each would be great to.
MA141 Grantham Week 5 Expected Value and Probability Paper
I need help with these questions. Also if a possible an explanation for each would be great to.
URGENT: mystatlab homework
i have 5 assignments left on mystatlab homework that is due tomorrow at 11:59. I've been scoring in the 90s on most of the ...
URGENT: mystatlab homework
i have 5 assignments left on mystatlab homework that is due tomorrow at 11:59. I've been scoring in the 90s on most of them but i am burnt and work all day tomorrow. Can someone help me?
AU Diabetic Medicare Enrollees Aged 65 to 75 Having Hemoglobin A1c Report
Assignment #1: Quantitative Analysis For
this assignment, students should choose data from the quantitative
analysis bel ...
AU Diabetic Medicare Enrollees Aged 65 to 75 Having Hemoglobin A1c Report
Assignment #1: Quantitative Analysis For
this assignment, students should choose data from the quantitative
analysis below and are asked to analyze it using Excel, RStuido (BONUS
points)Data set:Minnesota Healthcare Database.xlsxMedicare National Data by CountyMN Hospital Report Data by Care Unit FY2013MN HCCIS Imaging Procedures 2013MEPS Dental FilesMEPS Inpatient Stay DatabaseStudents
will develop an analysis report, in five main sections, including
introduction, research method (research questions/objective, data set,
research method, and analysis), results, conclusion and health policy
recommendations. This is a 5-6 page individual project report.Here are the main steps for this assignment.TOPIC: - Comparing average annual percent of diabetic Medicare enrollees age 65-75 having hemoglobin A1c between B and W (#1)Step 2: Develop the research question andStep 3: Run the analysis using EXCEL (RStudio for BONUS points) and report the findings using the assignment instruction.The Report Structure:Start with the1.Cover page (1 page, including running head).Please look at the example http://www.apastyle.org/manual/related/sample-experiment-paper-1.pdf (you can download the file from the class) and http://www.umgc.edu/library/libhow/apa_tutorial.cfm to learn more about the APA style.In the title page include:Title, this is the approved topic by your instructor.Student nameClass nameInstructor nameDate2.IntroductionIntroduce the problem or topic being investigated. Include relevant background information, for example; Indicates why this is an issue or topic worth researching;Highlight how others have researched this topic or issue (whether quantitatively or qualitatively), andSpecify how others have operationalized this concept and measured these phenomenaNote: Introduction should not be more than one or two paragraphs.Literature ReviewThere is no need for a literature review in this assignment3.Research Question or Research HypothesisWhat is the Research Question or Research Hypothesis?***Just in time information: Here are a few points for Research Question or Research HypothesisThere
are basically two kinds of research questions: testable and
non-testable. Neither is better than the other, and both have a place in
applied research.Examples of non-testable questions are:How do managers feel about the reorganization?What do residents feel are the most important problems facing the community?Respondents'
answers to these questions could be summarized in descriptive tables
and the results might be extremely valuable to administrators and
planners. Business and social science researchers often ask non-testable
research questions. The shortcoming with these types of questions is
that they do not provide objective cut-off points for decision-makers.In
order to overcome this problem, researchers often seek to answer one or
more testable research questions. Nearly all testable research
questions begin with one of the following two phrases:Is there a significant difference between ...?Is there a significant relationship between ...? For example:Is there a significant relationship between the age of managers? and their attitudes towards the reorganization?A
research hypothesis is a testable statement of opinion. It is created
from the research question by replacing the words "Is there" with the
words "There is," and also replacing the question mark with a period.
The hypotheses for the two sample research questions would be:There is a significant relationship between the age of managers and their attitudes towards the reorganization.
It is not possible to test a hypothesis directly. Instead, you must
turn the hypothesis into a null hypothesis. The null hypothesis is
created from the hypothesis by adding the words "no" or "not" to the
statement. For example, the null hypotheses for the two examples would
be:There is no significant relationship between the age of managersand their attitudes towards the reorganization.There is no significant difference between white and minority residentswith respect to what they feel are the most important problems facing the community.All
statistical testing is done on the null hypothesis...never the
hypothesis. The result of a statistical test will enable you to either:1) reject the null hypothesis, or2) fail to reject the null hypothesis. Never use the words "accept the null hypothesis." *Source:
StatPac for Windows Tutorial. (2017). User's Guide; Formulating
Hypotheses from Research Questions. Retrieved May 17, 2019 from https://statpac.com/manual/index.htm?turl=formulatinghypothesesfromresearchquestions.htmWhat does significance really mean?“Significance
is a statistical term that tells how sure you are that a difference or
relationship exists. To say that a significant difference or
relationship exists only tells half the story. We might be very sure
that a relationship exists, but is it a strong, moderate, or weak
relationship? After finding a significant relationship, it is important
to evaluate its strength. Significant relationships can be strong or
weak. Significant differences can be large or small. It just depends on
your sample size.To determine whether the observed difference is statistically significant, we look at two outputs of our statistical test:P-value:
The primary output of statistical tests is the p-value (probability
value). It indicates the probability of observing the difference if no
difference exists.The
p-value from above example, 0.9926, indicates that we DO NOT expect to
see a meaningless (random) difference of 5% or more in ‘hospital beds’
only about 993 times in 1000 there is no difference (0.9926*1000=992.6 ~
993).Note: This is an example from the week1 exercise.The
p-value from above example, 0.0001, indicates that we’d expect to see a
meaningless (random) ‘number of the employees on payer’ difference of
5% or more only about 0.1 times in 1000 (0.0001 * 1000=0.1). CI
around Difference: A confidence interval around a difference that does
not cross zero also indicates statistical significance. The graph below
shows the 95% confidence interval around the difference between hospital
beds in 2011 and 2012 (CI: [-40.82 ; 40.44]):CI around Difference: A confidence interval around a difference that does not cross zero also indicates statistical significance. The graph below shows the 95% confidence interval around the difference between hospital beds in 2011 and 2012 (CI: [-382.16 ; 125.53]):The
boundaries of this confidence interval around the difference also
provide a way to see what the upper [40.44] and lower bounds [-40.82].As a summary:“Statistically significant means a result is unlikely due to chance.The
p-value is the probability of obtaining the difference we saw from a
sample (or a larger one) if there really isn’t a difference for all
users.Statistical significance doesn’t mean practical
significance. Only by considering context can we determine whether a
difference is practically significant; that is, whether it requires
action.The confidence interval around the difference also
indicates statistical significance if the interval does not cross zero.
It also provides likely boundaries for any improvement to aide in
determining if a difference really is noteworthy.With large
sample sizes, you’re virtually certain to see statistically significant
results, in such situations, it’s important to interpret the size of the
difference”("Measuring U", 2019).*ResourceMeasuring U. (2019). Statistically significant. Retrieved May 17, 2019 from: https://measuringu.com/statistically-significant/Small
sample sizes often do not yield statistical significance; when they do,
the differences themselves tend also to be practically significant;
that is, meaningful enough to warrant action.4.Research MethodDiscuss
the Research Methodology (in general). Describe the variable or
variables that are being analyzed. Identify the statistical test you
will select to analyze these data and explain why you chose this test.
Summarize your statistical alternative hypothesis. This section includes
the following sub-sections:a)Describe the DatasetExample:
The primary source of data will be HOSPITAL COMPARE MEDICARE DATA
(citation). This dataset provides information on hospital
characteristics, such as: Number of staffed beds, ownership, system
membership, staffing by nurses and non-clinical staff, teaching status,
percentage of discharge for Medicare and Medicaid patients, and
information regarding the availability of specialty and high-tech
services, as well as Electronic Medical Record (EMR) use (Describe
dataset in 2-3 lines, Google the dataset and find the related website to
find more information about the data).Also, describe the sample
size; for example, “The writer is using Medicare data-2013, this data
includes 3000 obs. for all of the hospitals in the US.”b)Describe VariablesNext,
review the database you selected and select a variable or variables
that are a “best-fit.” That is, choose a variable that quantitatively
measures the concept or concepts articulated in your research question
or hypothesis. Return to your previously stated Research Question
or Hypothesis and evaluate it considering the variables you have
selected. (See the sample Table 1).Table 1. List of variables used for the analysisVariableDefinitionDescriptionof codeSourceYearTotal Hospital BedsTotal facility beds set up and staffedat the end of the reporting periodNumericMN Data2013….….. Source: UMGC, 2019 ***Just in time information:To cite a dataset, you can go with two approaches:First, look at the note in the dataset for example;Medicare National Data by County. (2012). Dartmouth Atlas of Health Care, A Second, use the online citation, for example:Zare,
H., (2019, May). MN Hospital Report Data. Data posted in University of
Maryland University College HMGT 400 online classroom, archived at: http://campus.umgc.eduSee two examples describing the variables from Minnesota Data:Table 2. Definition of variables used in the analysisVariableDefinitionDescriptionof codeSourceYearhospital_bedsTotal facility beds set up and staffedat the end of the reporting periodNumericMN data2013yearFYCategoricalMN data2013 Source: UMGC, 2019c)Describe the Research Method for AnalysisFirst,
describe the research method as a general (e.g., this is a quantitative
method and then explain about this method in about one paragraph. If
you have this part in the introduction, you do not need to add here).Then,
explain the statistical method you plan to use for your analysis (Refer
to content in week 3 on Biostatistics for information on various
statistical methods you can choose from).Example:Hypothesis: AZ hospitals are more likely to have lower readmission rates for PN compared to CA.Research
Method: To determine whether Arizona hospitals are more likely to have
lower readmission rate than California, we will use a t-test, to
determine whether differences across hospital types are statistically
significant (You can change the test depends on your analysis).d)Describe statistical packageAdd one paragraph for the statistical package, e.g., Excel or RStudio.5. ResultsDiscuss your findings considering the following tips:▪
Why you needed to see the distribution of data before any analysis
(e.g., check for outliers, finding the best fit test; for example, if
the data had not a normal distribution, you can’t use the parametric
test, etc., so just add 1 or 2 sentences).▪ Did you eliminate outliers? (Please write 1 or 2 sentences, if applicable).▪ How many observations do you have in your database and how many for selected variables, report % of missing.▪ When you are finished with this, go for the next steps:Present
the results of your statistical analysis; include any relevant
statistical information (summary tables, including N, mean, std. dev.).
Make sure to completely and correctly name all your columns and rows,
tables and variables. For this part you could have at least 1-2 tables
and 1-2 figures (depending on your variables bar-chart, pi-chart, or
scatter-plot), you can use a table like this:Table 3. Descriptive analysis to compare % of BL in Medicare beneficiary, MD vs. VA- 2013VariableObs.MeanSDP-valuePer of Lipid in MD2483.202.320.4064 Per of Lipid in VA 124 82.694.41 Source: UMGC, 2019When
you have tables and plots ready, think about your finding and state the
statistical conclusion. That is, do the results present evidence in
favor or the null hypothesis or evidence that contradicts the null
hypothesis?6.Conclusion and DiscussionReview your research questions or hypothesis. How
has your analysis informed this question or hypothesis? Present your
conclusion(s) from the results (presented above) and discuss the meaning
of this conclusion(s) considering the research question or hypothesis
presented in your introduction. At the end of this section, add
one or two sentences and discuss the limitations (including biases)
associated with this analysis and any other statements you think are
important in understanding the results of this analysis. ReferencesInclude
a reference page listing the bibliographic information for all sources
cited in this report. This information should be consistent with the
requirements specified in the American Psychological Association (APA)
format and style guide.
Use of Tessellations and The Type of Transformation Used and Why Paper
Create?a tessellation pattern using Microsoft®?Paint, GeoGebra, Microsoft®?PowerPoint®, or other means available to you ...
Use of Tessellations and The Type of Transformation Used and Why Paper
Create?a tessellation pattern using Microsoft®?Paint, GeoGebra, Microsoft®?PowerPoint®, or other means available to you and approved by the instructor; or you may draw something by hand. Refer to the following resources for help with creating a tessellation:
Tessellation Help
Drawing a Tessellation by Hand
Tessellation Example and Non-Example
Technology Resource Library
Use?color and shading to make your tessellation visually pleasing.
Write?a minimum 350-word?paper that includes the following:
An explanation of why you chose the tessellated figure
The type of transformation used and why
The actual tessellation or a picture of the created tessellation
Some real-world examples of tessellations that you can find
How you might use real-world examples of tessellations to help elementary-level students understand tessellations
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