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A line has a slope of
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2y+x=10......................................................................................................
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University of Houston Hand Wash Soap vs Sanitizer Project
Part I: Descriptive Draft (Descriptive Statistics)
choose a topic of interest and performing a simple experiment. The samp ...
University of Houston Hand Wash Soap vs Sanitizer Project
Part I: Descriptive Draft (Descriptive Statistics)
choose a topic of interest and performing a simple experiment. The sample size for experiments, at least 20. You will submit a descriptive draft to portray the data that was collected, explain the variable or variables being summarized and displayed, and why that variable was chosen. Organization of the descriptive draft should be as follows: (The Project Template is included on the final page of these instructions.)
· Introduction: One or two paragraphs introducing and detailing the project topic, how inquiry(ies) were conducted, and the relevance of the group’s project to a well-defined community. Include any national statistics that support the importance of the issue or that will be used for comparison to the data. This section should end with a one-sentence purpose statement and primary research question(s).
· Method: Two or three paragraphs containing the details of the group’s study, a description of the research objective(s)/hypothesis(es), type of study, participants, variables measured, and sampling technique. Numerical summaries and graphs of the data should be embedded throughout this section, along with the descriptions.
· Provide at least 3 different numerical summaries and displays of the data, as appropriate for the chosen topic and variable(s). Examples may include mean, median, standard deviation, 5-number summary, linear correlation coefficient, and/or linear regression equation; pie chart, Pareto chart, frequency/relative frequency distribution, histogram, stem-and-leaf plot, and/or scatter plot.
· Chapter 1 of the textbook provides helpful information about population parameters, sample statistics, sampling methods, and bias. Chapters 2, 3 and 4 provide helpful definitions, instructions and examples for summarizing and displaying both qualitative and quantitative data.
Part II: Final Draft (includes Inferential Statistics)
Each student will submit a final draft that answers a specific question or questions about a population defined by interest. Inferential statistics should include the following points: (The Project Template is included on the final page of these instructions.)
· Assumptions about the population, sampling distribution, or other facets of the investigation
· Clear hypotheses (e.g., null and alternative hypotheses) about one or more qualitative or quantitative variables of a well-defined population
· Findings: Analytical summaries such as confidence interval and/or P-value, including a proper interpretation
· Findings: Speculation upon the meaningfulness of results, as well as the limits and/or consequences of any statistical inferences
· Chapters 4, 9 and 10 of our e-text provide helpful definitions, instructions and examples for completing Part II, such as testing for linear correlation (chapter 4), interpreting confidence intervals (chapter 9), or formulating and interpreting hypothesis tests (chapter 10).
Students in the same SIP group will be using the same data. As such, each student in the same group may start with the same basic template, but each student must write her/his own Findings and Conclusions. Each student will submit their final draft in Canvas as a Microsoft Word document
The project will be based on Qualitative Experiment
Method
Several (at least 2-3) paragraphs that contain the details of your study, a description of your research objective(s)/hypothesis(es), type of study, participants, variables measured, and sampling technique. Numerical summaries and graphs of your data should be embedded throughout this section along with descriptions. See Part I: Descriptive Draft (Descriptive Statistics) of SIP-Assignment Instructions document.
Findings
Two to three paragraphs addressing inferential analyses and conclusions drawn about specific variables within a well-defined population (make clear null and alternative hypotheses). Identify assumptions made about your population, the sampling distribution of your sample statistic, or any other facet of your investigation, and the limits of your conclusions. Include a P-value and/or a confidence interval as needed and interpret it. Use visuals as necessary. See Part II: Final Draft (Inferential Statistics) of SIP-Assignment Instructions document.
Conclusion
One paragraph summary regarding the overall meaningfulness of the statistical inquiry and the lessons learned about project development and completion.
References
Cite any sources used to develop background information. Cite any source of national, state, or local statistics used as a null hypothesis.
Appendix
Raw data from the experiment or survey study must be included here. In addition, if an online survey was launched, a live link must be provided. Or, if live interviews or simple experiments were conducted, provide details such as dates, times, places, and names of group members involved.
University of California Davis Data Wrangling HTML Document
below are the questions and i will attach the note if you need ---title: "Question 1"---
```{r, message = FALSE}library(t ...
University of California Davis Data Wrangling HTML Document
below are the questions and i will attach the note if you need ---title: "Question 1"---
```{r, message = FALSE}library(tidyverse)library(gapminder)# use ?gapminder get the desciption of the dataset `gapminder````
Consider the dataset `gapminder`.
##### (a) Modify the `continent` factor by classifying the Americas' countries into `South America` and `North America` Hint: the following countries are in South America. ```r c("Argentina", "Bolivia", "Brazil", "Chile", "Colombia", "Ecuador", "Paraguay", "Peru", "Trinidad and Tobago", "Uruguay", "Venezuela") ```
In the following questions, use the dataset modified in (a).
Hint: you could use `case_when` function.
##### (b) How many countries are there in the dataset? How about for each continent?
##### (c) For each year, which country had the largest gdp per capital?
##### (d) For each continent, which country experienced the sharpest increment rate in life expectancy from 1997 to 2007?
##### (e) Focus on the data in year 2007, what are the correlation coefficients between life expectancy and gdp per capital for each continent?
##### (f) Visualize part (e) by plotting gdp per capital vs life expectancy.---title: "Question 2"---
Consider the `flights` dataset in the package `nycflights13`.
```{r, message = FALSE}library(nycflights13)library(tidyverse)```
##### (a) Add a column that is the amount of time gained in the air (`gain = dep_delay - arr_delay`)
##### (b) Sort part (a) descedingly by the column you just created. Store the result as `flights_gain`.
##### (c) On average, did flights gain or lose time? (Hint: not average gain, but as percentage of positive gain.)
##### (d) On average, did flights heading to SeaTac ("SEA") gain or loose time?
##### (e) Summerize the mean, min and max of the `air_time` column for flights from `JFK` to `SEA`.
##### (f) In which month was the average departure delay the greatest?
##### (g) In which airport were the average arrival delays the highest?
#####(h) Which city was flown to with the highest average speed?
##### (i) Create a data frame of the average arrival delay for each destination, then use` left_join` to join on the `airports` dataframe, which has the airport info. (Hint: read the documentation of `airports` for the airport codes.)---title: "Question 3"---
##### (a) There is a csv file called `groceries.csv` in this directory. Read the csv file using `read_csv` from `tidyverse` and store the data frame as `groceries`. The datset shows the prices of some common groceries item in 4 different stores.
The table shows the prices of different items in 4 different stores.
##### (b) Is the data frame in wide format or long format?
##### (c) Try to convert it into the other format. Store it as `groceries2`.
##### (d) Use a randomized block design to analysis the store prices. Is there a store marking up the item prices?
MATH 160 Cuyamaca College Module 4 Histogram Discussion Post
Progress CheckUse this activity to assess whether you and your peers can: Select an appropriate bin width for a histogram ...
MATH 160 Cuyamaca College Module 4 Histogram Discussion Post
Progress CheckUse this activity to assess whether you and your peers can: Select an appropriate bin width for a histogram and explain your choice.Use a histogram to describe the shape, center, and spread of a distribution of data.Learn by DoingThis is the first of several mini-labs designed to teach you how to use StatCrunch. Later in the course, you will be expected to complete more extensive labs and in-class quizzes/exams using the StatCrunch skills learned in these early mini-labs.Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer.Use the rubric at the bottom of this page as a guide for completing this assignment.A list of StatCrunch directions is provided after the Prompt section below.DirectionsSubmit your work:Carefully read all sections below (beginning with the Context section and ending with the Prompt section).Commit a good-faith effort to address all items in the Prompt section below. Please be sure to number your responses.If directed to do so, embed all required StatCrunch output in your initial submission. Please do not submit StatCrunch output as an attachment.Complete your assigned peer reviews:After you submit your initial good-faith attempt, continue to the ANSWER(S) page and review your instructor's response. But please do not submit your corrected work yet.Within three days after the due date, return to this assignment and complete your assigned peer reviews (directions (Links to an external site.)).Submit your corrected work:We all learn from mistakes (our own and our classmates' mistakes). So please do not immediately correct your own mistakes. If possible, wait until you receive feedback from at least one of your peers. If necessary, correct your work and resubmit the entire assignment - including any required StatCrunch output. Your instructor will only review and grade your most recent submission, so please do not refer to a previous submission.ContextWe will use the Best Actor Oscar winners (1970–2001) data file to learn how to create a histogram using StatCrunch, and to practice what we've learned about describing a histogram. We are interested in describing the distribution of actors' ages when they won the Best Actor Oscar.DataStart by downloading the actor datafile to your computer.Here are the directions for downloading the datafile.Here is the actor (Links to an external site.) datafile. (This is the "Excel" file. You do not need Excel installed on your device for this assignment.)Next you will create a histogram of the ages of Best Oscar winners and upload your histogram to your Stats-Class folder in Canvas. Here are the steps.open StatCrunch (directions). Upload the ages data file to StatCrunch (directions).Create a histogram of the ages of Best Actor Oscar winners (directions).Download the StatCrunch output window, your histogram (directions).PromptIn your initial post, respond to the following prompt. Describe the distribution of ages of the Best Actor Oscar winners. Your description should include: shape, center (a typical representative age), a typical interval of representative ages, spread (overall range of ages), and any outliers (unusual ages). Be sure to embed your histogram in your initial post (directions). Please do not submit your histogram as an attachment.Create a second histogram for the distribution of ages, and adjust the bin width (directions). Try both smaller and larger bin widths. Choose a bin width so that your second histogram does not look like the first. Upload your second histogram to your Stats-Class folder. Also embed your second histogram with your initial post. Indicate which histogram is better for analyzing the data (your first embedded histogram or your second). Explain why.List of StatCrunch DirectionsEach link will open in a new window. To return to this discussion, either close the new tab or select the tab for this discussion. Purchase StatCrunch (You only need to do this once.)Open StatCrunchDownload Excel FileUpload Excel Data File to StatCrunchDownload StatCrunch Output Window (no screenshots; please use these directions)Upload Files to Your Stats-Class Folder in CanvasEmbed Pictures in a Textbox (no attachments; please use these directions)Create a HistogramAdjust Histogram Bin WidthHere is a PDF document with all StatCrunch directions (Links to an external site.).RubricPeer Reviewed Assignment w/ StatCrunchPeer Reviewed Assignment w/ StatCrunchCriteriaRatingsPtsThis criterion is linked to a Learning OutcomeAddressing the Prompt6 ptsFull MarksAll parts of the Prompt are addressed. Answers are correct. Statistical vocabulary is used appropriately. Writing is clear and thought process is easy to follow.4 ptsPartial CreditSome parts of the prompt are not addressed, are incorrect, or are unclear.0 ptsNo MarksThe prompt is not addressed.6 ptsThis criterion is linked to a Learning OutcomeStatCrunch Data2 ptsFull MarksAppropriate StatCrunch graphs and/or tables are provided as directed.1 ptsPartial CreditStatCrunch graphs and tables are inappropriate or missing important information.0 ptsNo MarksNo StatCrunch information is provided.2 ptsThis criterion is linked to a Learning OutcomeIndividual Penalty0 ptsNo individual penalty-1 ptsIndividual penalty.Please see the instructor comments for more information.0 ptsThis criterion is linked to a Learning OutcomePeer Reviews2 ptsFull MarksYou completed all assigned peer reviews (maximum of 2). For each peer review, the points you assigned in the rubric are appropriate. You included comments explaining the score you posted in the rubric. If you deducted points in the rubric, your comments explain what the author needs to do to earn a higher grade when the teacher grades the assignment.1 ptsPartial CreditCommitted a good-faith effort to provide a high-quality peer review, but many necessary instructive comments are missing.0 ptsNo MarksNo peer review provided or the comments are not instructive.2 pts
Explore ANCOVA and Factorial ANOVA
one
Word document for this assignment. You will create this Word document
by cutting and pasting SPSS output into Word ...
Explore ANCOVA and Factorial ANOVA
one
Word document for this assignment. You will create this Word document
by cutting and pasting SPSS output into Word. Name the file in the
following format: lastnamefirstinitialPSY7107-9.doc (example:
smithbPSY7107-9.doc).Begin by downloading the following SPSS data setActivity 9.sav (found in Books and Resources for this Week)This
week’s assignment consists of two parts. In the first part, you will
utilize an existing dataset to compute a factorial ANOVA. All SPSS
output should be pasted into your Word document. In the second part, you
will be asked to create a hypothetical ANCOVA output table (for
variables related to your area of interest). Part A. SPSS AssignmentThe
“Activity 9.sav” file contains a dataset of a researcher interested in
finding the best way to educate elementary age children in mathematics.
In particular, she thinks that 5th grade girls do better in small class
sizes while boys excel in larger classes. Through the school district,
she has arranged a pilot program in which some classroom sizes are
reduced prior to the state-wide mathematics competency assessment. In
the dataset, you will find the following variables:Participant: unique identifierGender: Male (M) or Female (F)Classroom: Small (1) – no more than 10 childrenMedium (2) – between 11 and 19 childrenLarge (3) – 20 or more studentsScore – final score on the statewide competency assessment.Now do the following:Exploratory Data Analysis.Perform
exploratory data analysis on all variables in the data set. Realizing
that you have six groups, be sure that your exploratory analysis is
broken down by group. When possible, include appropriate graphs to help
illustrate the dataset.Give a one to two paragraph write up of the data once you have done this.Create an APA style table that presents descriptive statistics for the sample.Factorial ANOVA. Perform a factorial ANOVA using the “Activity 9.sav” data set.
Is
there a main effect of gender? If so, explain the effect. Use post hoc
tests when necessary (or explain why they are not required in this
specific case).Is
there a main effect of classroom size? If so, explain the effect. Use
post hoc tests when necessary (or explain why they are not required in
this specific case).Is there an interaction between your two variables? If so, using post hoc tests, describe these differences.Is
there support for the researcher’s hypothesis that girls would do
better than boys in classrooms with fewer students? Explain your answer.Write
up the results in APA style and interpret them. Be sure that you
discuss both main effects and the presence/absence of an interaction
between the two.Part B. Applying Analytical Strategies to an Area of Research InterestBriefly restate your research area of interest.Analysis
of Covariance. Using your area of interest, identify one independent
and two dependent variables, such that the dependent variables would
likely be covariates. Now, assume you conducted an ANCOVA that shows
both the first independent variable as well as the covariate
significantly predicts the dependent variable. Create a mock ANCOVA
output table (see SPSS Output 12.6 in your text for an example) that
supports the relationship shown above. Report your mock finding APA
style.You should now have the following file:lastnamefirstinitialPSY7107-9.doc (example: smithbPSY7107-9.doc)
mgsc 2207 question
Instructions:Name this file using three fields:: By submitting your assignment to the dropbox on Brightspace, you are agre ...
mgsc 2207 question
Instructions:Name this file using three fields:: By submitting your assignment to the dropbox on Brightspace, you are agreeing to the terms of the Compliance statement posted on Brightspace.: Assignments are to be done individually. Plagiarism will not be tolerated.: Submit (Attach) one file only to dropbox A1 in Brightspace.: Ensure that you file is not too big. It should be between 100 and 400 KB. If it is not, then pdf your file and compress it using the software found at:https://smallpdf.com/compress-pdf: To gain access to the dropbox you must have completed the Intro Quiz and Quizzes 1 & 2. Emailed assignments and overdue assignments will receive a mark of zero.: This assignment is a sampling of questions. To successfully complete the Tests, you will need to reference all of the material provided (lecture videos, live lectures, ppt, practice problems).: Be sure to back up all files related to your assignment.: If appropriate, please include references/citations. This is not necessary if you did the entire assignment on your own. The spacing in this file is a suggestion. Try to keep it to approximately 7 pages as in the original. YourLastNameYourFirstNameA1
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University of Houston Hand Wash Soap vs Sanitizer Project
Part I: Descriptive Draft (Descriptive Statistics)
choose a topic of interest and performing a simple experiment. The samp ...
University of Houston Hand Wash Soap vs Sanitizer Project
Part I: Descriptive Draft (Descriptive Statistics)
choose a topic of interest and performing a simple experiment. The sample size for experiments, at least 20. You will submit a descriptive draft to portray the data that was collected, explain the variable or variables being summarized and displayed, and why that variable was chosen. Organization of the descriptive draft should be as follows: (The Project Template is included on the final page of these instructions.)
· Introduction: One or two paragraphs introducing and detailing the project topic, how inquiry(ies) were conducted, and the relevance of the group’s project to a well-defined community. Include any national statistics that support the importance of the issue or that will be used for comparison to the data. This section should end with a one-sentence purpose statement and primary research question(s).
· Method: Two or three paragraphs containing the details of the group’s study, a description of the research objective(s)/hypothesis(es), type of study, participants, variables measured, and sampling technique. Numerical summaries and graphs of the data should be embedded throughout this section, along with the descriptions.
· Provide at least 3 different numerical summaries and displays of the data, as appropriate for the chosen topic and variable(s). Examples may include mean, median, standard deviation, 5-number summary, linear correlation coefficient, and/or linear regression equation; pie chart, Pareto chart, frequency/relative frequency distribution, histogram, stem-and-leaf plot, and/or scatter plot.
· Chapter 1 of the textbook provides helpful information about population parameters, sample statistics, sampling methods, and bias. Chapters 2, 3 and 4 provide helpful definitions, instructions and examples for summarizing and displaying both qualitative and quantitative data.
Part II: Final Draft (includes Inferential Statistics)
Each student will submit a final draft that answers a specific question or questions about a population defined by interest. Inferential statistics should include the following points: (The Project Template is included on the final page of these instructions.)
· Assumptions about the population, sampling distribution, or other facets of the investigation
· Clear hypotheses (e.g., null and alternative hypotheses) about one or more qualitative or quantitative variables of a well-defined population
· Findings: Analytical summaries such as confidence interval and/or P-value, including a proper interpretation
· Findings: Speculation upon the meaningfulness of results, as well as the limits and/or consequences of any statistical inferences
· Chapters 4, 9 and 10 of our e-text provide helpful definitions, instructions and examples for completing Part II, such as testing for linear correlation (chapter 4), interpreting confidence intervals (chapter 9), or formulating and interpreting hypothesis tests (chapter 10).
Students in the same SIP group will be using the same data. As such, each student in the same group may start with the same basic template, but each student must write her/his own Findings and Conclusions. Each student will submit their final draft in Canvas as a Microsoft Word document
The project will be based on Qualitative Experiment
Method
Several (at least 2-3) paragraphs that contain the details of your study, a description of your research objective(s)/hypothesis(es), type of study, participants, variables measured, and sampling technique. Numerical summaries and graphs of your data should be embedded throughout this section along with descriptions. See Part I: Descriptive Draft (Descriptive Statistics) of SIP-Assignment Instructions document.
Findings
Two to three paragraphs addressing inferential analyses and conclusions drawn about specific variables within a well-defined population (make clear null and alternative hypotheses). Identify assumptions made about your population, the sampling distribution of your sample statistic, or any other facet of your investigation, and the limits of your conclusions. Include a P-value and/or a confidence interval as needed and interpret it. Use visuals as necessary. See Part II: Final Draft (Inferential Statistics) of SIP-Assignment Instructions document.
Conclusion
One paragraph summary regarding the overall meaningfulness of the statistical inquiry and the lessons learned about project development and completion.
References
Cite any sources used to develop background information. Cite any source of national, state, or local statistics used as a null hypothesis.
Appendix
Raw data from the experiment or survey study must be included here. In addition, if an online survey was launched, a live link must be provided. Or, if live interviews or simple experiments were conducted, provide details such as dates, times, places, and names of group members involved.
University of California Davis Data Wrangling HTML Document
below are the questions and i will attach the note if you need ---title: "Question 1"---
```{r, message = FALSE}library(t ...
University of California Davis Data Wrangling HTML Document
below are the questions and i will attach the note if you need ---title: "Question 1"---
```{r, message = FALSE}library(tidyverse)library(gapminder)# use ?gapminder get the desciption of the dataset `gapminder````
Consider the dataset `gapminder`.
##### (a) Modify the `continent` factor by classifying the Americas' countries into `South America` and `North America` Hint: the following countries are in South America. ```r c("Argentina", "Bolivia", "Brazil", "Chile", "Colombia", "Ecuador", "Paraguay", "Peru", "Trinidad and Tobago", "Uruguay", "Venezuela") ```
In the following questions, use the dataset modified in (a).
Hint: you could use `case_when` function.
##### (b) How many countries are there in the dataset? How about for each continent?
##### (c) For each year, which country had the largest gdp per capital?
##### (d) For each continent, which country experienced the sharpest increment rate in life expectancy from 1997 to 2007?
##### (e) Focus on the data in year 2007, what are the correlation coefficients between life expectancy and gdp per capital for each continent?
##### (f) Visualize part (e) by plotting gdp per capital vs life expectancy.---title: "Question 2"---
Consider the `flights` dataset in the package `nycflights13`.
```{r, message = FALSE}library(nycflights13)library(tidyverse)```
##### (a) Add a column that is the amount of time gained in the air (`gain = dep_delay - arr_delay`)
##### (b) Sort part (a) descedingly by the column you just created. Store the result as `flights_gain`.
##### (c) On average, did flights gain or lose time? (Hint: not average gain, but as percentage of positive gain.)
##### (d) On average, did flights heading to SeaTac ("SEA") gain or loose time?
##### (e) Summerize the mean, min and max of the `air_time` column for flights from `JFK` to `SEA`.
##### (f) In which month was the average departure delay the greatest?
##### (g) In which airport were the average arrival delays the highest?
#####(h) Which city was flown to with the highest average speed?
##### (i) Create a data frame of the average arrival delay for each destination, then use` left_join` to join on the `airports` dataframe, which has the airport info. (Hint: read the documentation of `airports` for the airport codes.)---title: "Question 3"---
##### (a) There is a csv file called `groceries.csv` in this directory. Read the csv file using `read_csv` from `tidyverse` and store the data frame as `groceries`. The datset shows the prices of some common groceries item in 4 different stores.
The table shows the prices of different items in 4 different stores.
##### (b) Is the data frame in wide format or long format?
##### (c) Try to convert it into the other format. Store it as `groceries2`.
##### (d) Use a randomized block design to analysis the store prices. Is there a store marking up the item prices?
MATH 160 Cuyamaca College Module 4 Histogram Discussion Post
Progress CheckUse this activity to assess whether you and your peers can: Select an appropriate bin width for a histogram ...
MATH 160 Cuyamaca College Module 4 Histogram Discussion Post
Progress CheckUse this activity to assess whether you and your peers can: Select an appropriate bin width for a histogram and explain your choice.Use a histogram to describe the shape, center, and spread of a distribution of data.Learn by DoingThis is the first of several mini-labs designed to teach you how to use StatCrunch. Later in the course, you will be expected to complete more extensive labs and in-class quizzes/exams using the StatCrunch skills learned in these early mini-labs.Some features of this activity may not work well on a cell phone or tablet. We highly recommend that you complete this activity on a computer.Use the rubric at the bottom of this page as a guide for completing this assignment.A list of StatCrunch directions is provided after the Prompt section below.DirectionsSubmit your work:Carefully read all sections below (beginning with the Context section and ending with the Prompt section).Commit a good-faith effort to address all items in the Prompt section below. Please be sure to number your responses.If directed to do so, embed all required StatCrunch output in your initial submission. Please do not submit StatCrunch output as an attachment.Complete your assigned peer reviews:After you submit your initial good-faith attempt, continue to the ANSWER(S) page and review your instructor's response. But please do not submit your corrected work yet.Within three days after the due date, return to this assignment and complete your assigned peer reviews (directions (Links to an external site.)).Submit your corrected work:We all learn from mistakes (our own and our classmates' mistakes). So please do not immediately correct your own mistakes. If possible, wait until you receive feedback from at least one of your peers. If necessary, correct your work and resubmit the entire assignment - including any required StatCrunch output. Your instructor will only review and grade your most recent submission, so please do not refer to a previous submission.ContextWe will use the Best Actor Oscar winners (1970–2001) data file to learn how to create a histogram using StatCrunch, and to practice what we've learned about describing a histogram. We are interested in describing the distribution of actors' ages when they won the Best Actor Oscar.DataStart by downloading the actor datafile to your computer.Here are the directions for downloading the datafile.Here is the actor (Links to an external site.) datafile. (This is the "Excel" file. You do not need Excel installed on your device for this assignment.)Next you will create a histogram of the ages of Best Oscar winners and upload your histogram to your Stats-Class folder in Canvas. Here are the steps.open StatCrunch (directions). Upload the ages data file to StatCrunch (directions).Create a histogram of the ages of Best Actor Oscar winners (directions).Download the StatCrunch output window, your histogram (directions).PromptIn your initial post, respond to the following prompt. Describe the distribution of ages of the Best Actor Oscar winners. Your description should include: shape, center (a typical representative age), a typical interval of representative ages, spread (overall range of ages), and any outliers (unusual ages). Be sure to embed your histogram in your initial post (directions). Please do not submit your histogram as an attachment.Create a second histogram for the distribution of ages, and adjust the bin width (directions). Try both smaller and larger bin widths. Choose a bin width so that your second histogram does not look like the first. Upload your second histogram to your Stats-Class folder. Also embed your second histogram with your initial post. Indicate which histogram is better for analyzing the data (your first embedded histogram or your second). Explain why.List of StatCrunch DirectionsEach link will open in a new window. To return to this discussion, either close the new tab or select the tab for this discussion. Purchase StatCrunch (You only need to do this once.)Open StatCrunchDownload Excel FileUpload Excel Data File to StatCrunchDownload StatCrunch Output Window (no screenshots; please use these directions)Upload Files to Your Stats-Class Folder in CanvasEmbed Pictures in a Textbox (no attachments; please use these directions)Create a HistogramAdjust Histogram Bin WidthHere is a PDF document with all StatCrunch directions (Links to an external site.).RubricPeer Reviewed Assignment w/ StatCrunchPeer Reviewed Assignment w/ StatCrunchCriteriaRatingsPtsThis criterion is linked to a Learning OutcomeAddressing the Prompt6 ptsFull MarksAll parts of the Prompt are addressed. Answers are correct. Statistical vocabulary is used appropriately. Writing is clear and thought process is easy to follow.4 ptsPartial CreditSome parts of the prompt are not addressed, are incorrect, or are unclear.0 ptsNo MarksThe prompt is not addressed.6 ptsThis criterion is linked to a Learning OutcomeStatCrunch Data2 ptsFull MarksAppropriate StatCrunch graphs and/or tables are provided as directed.1 ptsPartial CreditStatCrunch graphs and tables are inappropriate or missing important information.0 ptsNo MarksNo StatCrunch information is provided.2 ptsThis criterion is linked to a Learning OutcomeIndividual Penalty0 ptsNo individual penalty-1 ptsIndividual penalty.Please see the instructor comments for more information.0 ptsThis criterion is linked to a Learning OutcomePeer Reviews2 ptsFull MarksYou completed all assigned peer reviews (maximum of 2). For each peer review, the points you assigned in the rubric are appropriate. You included comments explaining the score you posted in the rubric. If you deducted points in the rubric, your comments explain what the author needs to do to earn a higher grade when the teacher grades the assignment.1 ptsPartial CreditCommitted a good-faith effort to provide a high-quality peer review, but many necessary instructive comments are missing.0 ptsNo MarksNo peer review provided or the comments are not instructive.2 pts
Explore ANCOVA and Factorial ANOVA
one
Word document for this assignment. You will create this Word document
by cutting and pasting SPSS output into Word ...
Explore ANCOVA and Factorial ANOVA
one
Word document for this assignment. You will create this Word document
by cutting and pasting SPSS output into Word. Name the file in the
following format: lastnamefirstinitialPSY7107-9.doc (example:
smithbPSY7107-9.doc).Begin by downloading the following SPSS data setActivity 9.sav (found in Books and Resources for this Week)This
week’s assignment consists of two parts. In the first part, you will
utilize an existing dataset to compute a factorial ANOVA. All SPSS
output should be pasted into your Word document. In the second part, you
will be asked to create a hypothetical ANCOVA output table (for
variables related to your area of interest). Part A. SPSS AssignmentThe
“Activity 9.sav” file contains a dataset of a researcher interested in
finding the best way to educate elementary age children in mathematics.
In particular, she thinks that 5th grade girls do better in small class
sizes while boys excel in larger classes. Through the school district,
she has arranged a pilot program in which some classroom sizes are
reduced prior to the state-wide mathematics competency assessment. In
the dataset, you will find the following variables:Participant: unique identifierGender: Male (M) or Female (F)Classroom: Small (1) – no more than 10 childrenMedium (2) – between 11 and 19 childrenLarge (3) – 20 or more studentsScore – final score on the statewide competency assessment.Now do the following:Exploratory Data Analysis.Perform
exploratory data analysis on all variables in the data set. Realizing
that you have six groups, be sure that your exploratory analysis is
broken down by group. When possible, include appropriate graphs to help
illustrate the dataset.Give a one to two paragraph write up of the data once you have done this.Create an APA style table that presents descriptive statistics for the sample.Factorial ANOVA. Perform a factorial ANOVA using the “Activity 9.sav” data set.
Is
there a main effect of gender? If so, explain the effect. Use post hoc
tests when necessary (or explain why they are not required in this
specific case).Is
there a main effect of classroom size? If so, explain the effect. Use
post hoc tests when necessary (or explain why they are not required in
this specific case).Is there an interaction between your two variables? If so, using post hoc tests, describe these differences.Is
there support for the researcher’s hypothesis that girls would do
better than boys in classrooms with fewer students? Explain your answer.Write
up the results in APA style and interpret them. Be sure that you
discuss both main effects and the presence/absence of an interaction
between the two.Part B. Applying Analytical Strategies to an Area of Research InterestBriefly restate your research area of interest.Analysis
of Covariance. Using your area of interest, identify one independent
and two dependent variables, such that the dependent variables would
likely be covariates. Now, assume you conducted an ANCOVA that shows
both the first independent variable as well as the covariate
significantly predicts the dependent variable. Create a mock ANCOVA
output table (see SPSS Output 12.6 in your text for an example) that
supports the relationship shown above. Report your mock finding APA
style.You should now have the following file:lastnamefirstinitialPSY7107-9.doc (example: smithbPSY7107-9.doc)
mgsc 2207 question
Instructions:Name this file using three fields:: By submitting your assignment to the dropbox on Brightspace, you are agre ...
mgsc 2207 question
Instructions:Name this file using three fields:: By submitting your assignment to the dropbox on Brightspace, you are agreeing to the terms of the Compliance statement posted on Brightspace.: Assignments are to be done individually. Plagiarism will not be tolerated.: Submit (Attach) one file only to dropbox A1 in Brightspace.: Ensure that you file is not too big. It should be between 100 and 400 KB. If it is not, then pdf your file and compress it using the software found at:https://smallpdf.com/compress-pdf: To gain access to the dropbox you must have completed the Intro Quiz and Quizzes 1 & 2. Emailed assignments and overdue assignments will receive a mark of zero.: This assignment is a sampling of questions. To successfully complete the Tests, you will need to reference all of the material provided (lecture videos, live lectures, ppt, practice problems).: Be sure to back up all files related to your assignment.: If appropriate, please include references/citations. This is not necessary if you did the entire assignment on your own. The spacing in this file is a suggestion. Try to keep it to approximately 7 pages as in the original. YourLastNameYourFirstNameA1
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