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I need help fast . Q.1) A wheel has diameter of 84 cm. Find how many complete revolution must It take to cover 792 mtrs. Q.2) A boy is cycling such that the wheels of the cycle are making 140 revolutions per minute. If diameter is 60 cm find speed of the boy cycling per hour.
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Grand Canyon University T Statisitcs Test Questions Discussion
Question 1- Explain why using the t statistic may be an appropriate alternative to
using a z-score (use the concept of e ...
Grand Canyon University T Statisitcs Test Questions Discussion
Question 1- Explain why using the t statistic may be an appropriate alternative to
using a z-score (use the concept of estimated standard error to justify
your answer).Question 2 -Discuss how the t-test for correlated groups and the t-test for single samples are alike and different.
Quantitative Analysis and Decision Making
Understanding of probability is key in making business decisions. The following questions begin to test your understanding ...
Quantitative Analysis and Decision Making
Understanding of probability is key in making business decisions. The following questions begin to test your understanding of the different forms of probability and the data on which probabilistic decision making is based.Select any one of the following starter bullet point sections. Review the important themes within the sub questions of each bullet point. The sub questions are designed to get you thinking about some of the important issues. Your response should provide a succinct synthesis of the key themes in a way that articulates a clear point, position, or conclusion supported by research. Select a different bullet point section than what your classmates have already posted so that we can engage several discussions on relevant topics. If all of the bullet points have been addressed, then you may begin to re-use the bullet points with the expectation that varied responses continue.You are a risk manager in a manufacturing company. One of your key responsibilities is securing of property insurance coverage to provide protection against damage caused by “acts of God,” such as earthquakes, hurricanes, floods, etc. You begin the process with exposure due diligence, which is focused on estimating the chances of a single “act of God” occurring in the course of the upcoming year, as well as the chances of two or more “acts of God” materializing (also in the course of the next year).Determine where you might be able to find valid data for this type of analysis.Justify the use of the concept of conditional probability in the context of your task—more specifically, discuss how you would use conditional probability in your exposure due diligence efforts. Support your discussion with relevant examples, research, and rationale.You are a marketing manager for a company that makes ready-to-eat breakfast cereals. Your company recently initiated a loyalty program for consumers, which resulted in a large purchaser database. The brand managers are eager to examine the available data, which they can use to design more effective promotional programs. Your first step is to conduct an exploratory baseline analysis, the goal of which is to describe the buyer base and estimate basic statistical descriptors of the buyer base. You are particularly interested in the size of individual purchases, as well as the frequency of repurchases.Evaluate what discrete data distribution the frequency of repurchases data would be likely to follow.Explain why the other discrete data distributions are not appropriate for this data. Support your discussion with relevant examples, research, and rationale.You are a marketing manager for a manufacturer of nonperishable products sold in grocery stores. In this role, you need to make various decisions about how much marketing/advertising support is needed by each product to maximize the profitability of the organization.Assess how the effectiveness of individual marketing/advertising approaches would be determined.Discuss how historical sales data, as well as promotional response data, can aid you in evaluating the effectiveness of the individual marketing/advertising approaches. Support your discussion with relevant examples, research, and rationale.The final paragraph (three or four sentences) of your initial post should summarize the one or two key points that you are making in your initial response.Your posting should be the equivalent of 1 to 2 single-spaced pages (500–1000 words) in length.
BTM8107-8 Statistics II Week 5
Part A. SPSS AssignmentThe “Activity 5.sav” file contains a dataset of a researcher interested in finding the best way ...
BTM8107-8 Statistics II Week 5
Part A. SPSS AssignmentThe “Activity 5.sav” file contains a dataset of a researcher interested in finding the best way to educate elementary age children in mathematics. In particular, she believes 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 childrenScore: final score on the statewide competency assessment.To complete this assignmentExploratory 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.Compose a one to two paragraph write up of the data.Create an APA style table that presents descriptive statistics for the sample.Factorial ANOVA. Perform a factorial ANOVA using the “Activity 5.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 dependent and two independent variables, such that the independent variables would likely be covariates. Now, assume you conducted an ANCOVA that shows both the independent variable as well as the covariate significantly predicts the dependent variable. Create a mock ANCOVA output table (see SPSS Output 11.3 in your text for an example) that supports the relationship shown above. Report your mock finding APA style.
need answers to these multiple choice math problems? details below
description of question below_________________________________________________________________________ ___________________ ...
need answers to these multiple choice math problems? details below
description of question below_________________________________________________________________________ ______________________________________________all of them are multiple choice questions
Moore College of Art and Design ANOVA F Test Using StatCrunch Project
Learn by DoingThe purpose of this activity is to give you guided practice in carrying out the ANOVA F-test using StatCrunc ...
Moore College of Art and Design ANOVA F Test Using StatCrunch Project
Learn by DoingThe purpose of this activity is to give you guided practice in carrying out the ANOVA F-test using StatCrunch.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.Here are the directions and grading rubric for the discussion board exercises. A list of StatCrunch directions is provided at the bottom of this page.ContextCritical flicker frequency (CFF) and eye colorComputer screens and fluorescent bulbs flicker. If the
frequency of the flicker is below a certain threshold, the eye detects
the flicker, and it is annoying!Different people have different flicker "threshold" frequencies (known as the critical flicker frequency, or CFF). The mean critical threshold frequency is important for product manufacturing as well as tests for ocular disease.In 1973, researchers conducted a study to answer the following question.Research question: Do people with different eye color have different threshold flicker sensitivity?The 1973 study ("The Effect of Iris Color on Critical Flicker Frequency," Journal of General Psychology [1973], 91–95) obtained the following data from a random sample of 19 subjects.
Color
ThresholdFrequency (CFF)
Blue
Brown
Green
Brown
26.8
25.7
26.8
26.4
Brown
27.9
27.2
27.9
24.2
Brown
23.7
29.9
23.7
28
Brown
25.0
28.5
25
26.9
Brown
26.3
29.4
26.3
29.1
Brown
24.8
28.3
24.8
Brown
25.7
25.7
Brown
24.5
24.5
Green
26.4
Green
24.2
Green
28.0
Green
26.9
Green
29.1
Blue
25.7
Blue
27.2
Blue
29.9
Blue
28.5
Blue
29.4
Blue
28.3
In this spreadsheet the data is presented in two formats.Stacked data: The quantitative data is stacked in one column. The first two columns show the data in a stacked format.
Each variable is a column (one column for the explanatory variable eye
color; one column for the response variable CFF) and each row is an
individual. For example, the first row is a brown-eyed person with a CFF
of 26.8.Unstacked data: The quantitative data is distributed across the groups in multiple columns. The last three columns show the same data in an unstacked format.
In this format, each column is a group defined by a value of the
explanatory variable: one column for blue-eyed people, one column for
brown-eyed people and one column for green-eyed people. Each column
contains the response values (CFF) for that group.The format of the data in the spreadsheet affects how we use StatCrunch to analyze it.VariablesColor: This is the explanatory variable. The categorical data represents the groups we will compare.CFF (flicker threshold sensitivity): This is the response variable. The quantitative data represents the frequency threshold at which the subject sees the flicker. use the Data below PromptWe will conduct an ANOVA F-test for the variables Color and CFF. The flicker datafile is available in the Data section below. Also, the StatCrunch directions are provided in the list a the bottom of this page.What are the hypotheses for the ANOVA test? Be sure that you define clearly the parameters.
Are the conditions that allow us to safely use the ANOVA F-test met? Explain.Note:
To verify conditions, you will need to examine the distribution of CFF
scores for each sample (because the samples are small).
Use StatCrunch to create side-by-side dotplots, histograms or
boxplots (your choice) to examine the distribution of CFF scores for
each sample. You can use either data format; choose one (stacked data in the first two columns; or unstacked data
in the the last three columns). To create the side-by-side graphs (for
either data format) see the list of StatCrunch directions below.
Download the StatCrunch output window (your graph), upload it to your Stats-Class
folder, and then embed the .png file (your graph) in your initial post.
To recall how to complete these tasks, see the list of StatCrunch
directions below.
You will also need to compare the sample standard deviations. Use
StatCrunch to find the summary statistics, means and standard deviations
for the comparison groups (select the the appropriate Descriptive
Statistics StatCrunch directions from the list below). Then copy and
paste the table into your initial post and explain how the rule of thumb for comparing standard deviations is met.
Use StatCrunch to carry out the ANOVA F-test (select the appropriate
ANOVA StatCrunch directions from the following two options). Copy and paste the output table into your initial post.
State your conclusion in context of eye color and mean CFF.
STA 1625 Rasmussen College Binomial Probabilities Statistics Questions
Gaming and probability are intertwined. In fact, there is an entire discipline in mathematics called “Game Theory.” In ...
STA 1625 Rasmussen College Binomial Probabilities Statistics Questions
Gaming and probability are intertwined. In fact, there is an entire discipline in mathematics called “Game Theory.” In this assessment, you will apply discrete and continuous probability distributions to games. There will be two parts: the first will concentrate on discrete probability distributions, and the second part will focus on continuous probability distributions.InstructionsPart One - Data TableThe theoretical probability of rolling a fair six-sided die is 1/6 for any specific single outcome, such as rolling a one. You want to test the theoretical probability by running an experiment.In this experiment, you need to roll a six-sided die 25 times. Record the outcome of each die roll. Create a discrete probability distribution using your outcomes as the probability. For example, if you rolled 4 fives out of your 25 total rolls, your probability would be 4/25.x123456P(x)Part Two - Discrete Probability DistributionAfter filling in the table above with your experimental probability, answer the following questions. Show all work for full credit. Calculations should be performed in Excel while answers including an explanation of steps using proper terminology are provided in a separate document.1. What is the expected outcome for rolling a six-sided die using the discrete probability distribution table above?2. What is the probability of rolling an even number according to the discrete probability distribution table above?How does this compare to the theoretical probability of 0.5?Explain why you think there is a difference between the theoretical probability and the experimental probability you found.3. Create a binomial probability distribution based on the discrete probability distribution table above where a success is rolling an even number. Answer the following questions:How do you know this is a Binomial Probability Distribution? Explain by showing how this example fits all four properties of a Binomial Probability Distribution.Define n,p,q.What is the probability that you will roll exactly 12 even numbers?What is the probability that you will roll at least 12 even numbers?Find the expected number of even numbers that you will roll.Part Three - Continuous Probability DistributionDice are a common tool used in several board games. One board game which utilizes two dice is Monopoly. While the outcomes of rolling two dice in this game would be a discrete random variable, we are interested in looking at a continuous random variable associated with Monopoly and its respective probability.The time it takes to finish a game of Monopoly is normally distributed with a mean of 120 minutes and a standard deviation of 30 minutes. Using this premise, answer the following questions. Show all work for full credit. Calculations should be performed in Excel while answers including an explanation of steps using proper terminology are provided in a separate document.Explain why this is a continuous probability distribution instead of a discrete probability distribution.What is the probability that a game lasts less than 45 minutes?What is the probability that a game lasts more than 160 minutes?What is the z-score of a game that lasts exactly 105 minutes?
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Grand Canyon University T Statisitcs Test Questions Discussion
Question 1- Explain why using the t statistic may be an appropriate alternative to
using a z-score (use the concept of e ...
Grand Canyon University T Statisitcs Test Questions Discussion
Question 1- Explain why using the t statistic may be an appropriate alternative to
using a z-score (use the concept of estimated standard error to justify
your answer).Question 2 -Discuss how the t-test for correlated groups and the t-test for single samples are alike and different.
Quantitative Analysis and Decision Making
Understanding of probability is key in making business decisions. The following questions begin to test your understanding ...
Quantitative Analysis and Decision Making
Understanding of probability is key in making business decisions. The following questions begin to test your understanding of the different forms of probability and the data on which probabilistic decision making is based.Select any one of the following starter bullet point sections. Review the important themes within the sub questions of each bullet point. The sub questions are designed to get you thinking about some of the important issues. Your response should provide a succinct synthesis of the key themes in a way that articulates a clear point, position, or conclusion supported by research. Select a different bullet point section than what your classmates have already posted so that we can engage several discussions on relevant topics. If all of the bullet points have been addressed, then you may begin to re-use the bullet points with the expectation that varied responses continue.You are a risk manager in a manufacturing company. One of your key responsibilities is securing of property insurance coverage to provide protection against damage caused by “acts of God,” such as earthquakes, hurricanes, floods, etc. You begin the process with exposure due diligence, which is focused on estimating the chances of a single “act of God” occurring in the course of the upcoming year, as well as the chances of two or more “acts of God” materializing (also in the course of the next year).Determine where you might be able to find valid data for this type of analysis.Justify the use of the concept of conditional probability in the context of your task—more specifically, discuss how you would use conditional probability in your exposure due diligence efforts. Support your discussion with relevant examples, research, and rationale.You are a marketing manager for a company that makes ready-to-eat breakfast cereals. Your company recently initiated a loyalty program for consumers, which resulted in a large purchaser database. The brand managers are eager to examine the available data, which they can use to design more effective promotional programs. Your first step is to conduct an exploratory baseline analysis, the goal of which is to describe the buyer base and estimate basic statistical descriptors of the buyer base. You are particularly interested in the size of individual purchases, as well as the frequency of repurchases.Evaluate what discrete data distribution the frequency of repurchases data would be likely to follow.Explain why the other discrete data distributions are not appropriate for this data. Support your discussion with relevant examples, research, and rationale.You are a marketing manager for a manufacturer of nonperishable products sold in grocery stores. In this role, you need to make various decisions about how much marketing/advertising support is needed by each product to maximize the profitability of the organization.Assess how the effectiveness of individual marketing/advertising approaches would be determined.Discuss how historical sales data, as well as promotional response data, can aid you in evaluating the effectiveness of the individual marketing/advertising approaches. Support your discussion with relevant examples, research, and rationale.The final paragraph (three or four sentences) of your initial post should summarize the one or two key points that you are making in your initial response.Your posting should be the equivalent of 1 to 2 single-spaced pages (500–1000 words) in length.
BTM8107-8 Statistics II Week 5
Part A. SPSS AssignmentThe “Activity 5.sav” file contains a dataset of a researcher interested in finding the best way ...
BTM8107-8 Statistics II Week 5
Part A. SPSS AssignmentThe “Activity 5.sav” file contains a dataset of a researcher interested in finding the best way to educate elementary age children in mathematics. In particular, she believes 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 childrenScore: final score on the statewide competency assessment.To complete this assignmentExploratory 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.Compose a one to two paragraph write up of the data.Create an APA style table that presents descriptive statistics for the sample.Factorial ANOVA. Perform a factorial ANOVA using the “Activity 5.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 dependent and two independent variables, such that the independent variables would likely be covariates. Now, assume you conducted an ANCOVA that shows both the independent variable as well as the covariate significantly predicts the dependent variable. Create a mock ANCOVA output table (see SPSS Output 11.3 in your text for an example) that supports the relationship shown above. Report your mock finding APA style.
need answers to these multiple choice math problems? details below
description of question below_________________________________________________________________________ ___________________ ...
need answers to these multiple choice math problems? details below
description of question below_________________________________________________________________________ ______________________________________________all of them are multiple choice questions
Moore College of Art and Design ANOVA F Test Using StatCrunch Project
Learn by DoingThe purpose of this activity is to give you guided practice in carrying out the ANOVA F-test using StatCrunc ...
Moore College of Art and Design ANOVA F Test Using StatCrunch Project
Learn by DoingThe purpose of this activity is to give you guided practice in carrying out the ANOVA F-test using StatCrunch.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.Here are the directions and grading rubric for the discussion board exercises. A list of StatCrunch directions is provided at the bottom of this page.ContextCritical flicker frequency (CFF) and eye colorComputer screens and fluorescent bulbs flicker. If the
frequency of the flicker is below a certain threshold, the eye detects
the flicker, and it is annoying!Different people have different flicker "threshold" frequencies (known as the critical flicker frequency, or CFF). The mean critical threshold frequency is important for product manufacturing as well as tests for ocular disease.In 1973, researchers conducted a study to answer the following question.Research question: Do people with different eye color have different threshold flicker sensitivity?The 1973 study ("The Effect of Iris Color on Critical Flicker Frequency," Journal of General Psychology [1973], 91–95) obtained the following data from a random sample of 19 subjects.
Color
ThresholdFrequency (CFF)
Blue
Brown
Green
Brown
26.8
25.7
26.8
26.4
Brown
27.9
27.2
27.9
24.2
Brown
23.7
29.9
23.7
28
Brown
25.0
28.5
25
26.9
Brown
26.3
29.4
26.3
29.1
Brown
24.8
28.3
24.8
Brown
25.7
25.7
Brown
24.5
24.5
Green
26.4
Green
24.2
Green
28.0
Green
26.9
Green
29.1
Blue
25.7
Blue
27.2
Blue
29.9
Blue
28.5
Blue
29.4
Blue
28.3
In this spreadsheet the data is presented in two formats.Stacked data: The quantitative data is stacked in one column. The first two columns show the data in a stacked format.
Each variable is a column (one column for the explanatory variable eye
color; one column for the response variable CFF) and each row is an
individual. For example, the first row is a brown-eyed person with a CFF
of 26.8.Unstacked data: The quantitative data is distributed across the groups in multiple columns. The last three columns show the same data in an unstacked format.
In this format, each column is a group defined by a value of the
explanatory variable: one column for blue-eyed people, one column for
brown-eyed people and one column for green-eyed people. Each column
contains the response values (CFF) for that group.The format of the data in the spreadsheet affects how we use StatCrunch to analyze it.VariablesColor: This is the explanatory variable. The categorical data represents the groups we will compare.CFF (flicker threshold sensitivity): This is the response variable. The quantitative data represents the frequency threshold at which the subject sees the flicker. use the Data below PromptWe will conduct an ANOVA F-test for the variables Color and CFF. The flicker datafile is available in the Data section below. Also, the StatCrunch directions are provided in the list a the bottom of this page.What are the hypotheses for the ANOVA test? Be sure that you define clearly the parameters.
Are the conditions that allow us to safely use the ANOVA F-test met? Explain.Note:
To verify conditions, you will need to examine the distribution of CFF
scores for each sample (because the samples are small).
Use StatCrunch to create side-by-side dotplots, histograms or
boxplots (your choice) to examine the distribution of CFF scores for
each sample. You can use either data format; choose one (stacked data in the first two columns; or unstacked data
in the the last three columns). To create the side-by-side graphs (for
either data format) see the list of StatCrunch directions below.
Download the StatCrunch output window (your graph), upload it to your Stats-Class
folder, and then embed the .png file (your graph) in your initial post.
To recall how to complete these tasks, see the list of StatCrunch
directions below.
You will also need to compare the sample standard deviations. Use
StatCrunch to find the summary statistics, means and standard deviations
for the comparison groups (select the the appropriate Descriptive
Statistics StatCrunch directions from the list below). Then copy and
paste the table into your initial post and explain how the rule of thumb for comparing standard deviations is met.
Use StatCrunch to carry out the ANOVA F-test (select the appropriate
ANOVA StatCrunch directions from the following two options). Copy and paste the output table into your initial post.
State your conclusion in context of eye color and mean CFF.
STA 1625 Rasmussen College Binomial Probabilities Statistics Questions
Gaming and probability are intertwined. In fact, there is an entire discipline in mathematics called “Game Theory.” In ...
STA 1625 Rasmussen College Binomial Probabilities Statistics Questions
Gaming and probability are intertwined. In fact, there is an entire discipline in mathematics called “Game Theory.” In this assessment, you will apply discrete and continuous probability distributions to games. There will be two parts: the first will concentrate on discrete probability distributions, and the second part will focus on continuous probability distributions.InstructionsPart One - Data TableThe theoretical probability of rolling a fair six-sided die is 1/6 for any specific single outcome, such as rolling a one. You want to test the theoretical probability by running an experiment.In this experiment, you need to roll a six-sided die 25 times. Record the outcome of each die roll. Create a discrete probability distribution using your outcomes as the probability. For example, if you rolled 4 fives out of your 25 total rolls, your probability would be 4/25.x123456P(x)Part Two - Discrete Probability DistributionAfter filling in the table above with your experimental probability, answer the following questions. Show all work for full credit. Calculations should be performed in Excel while answers including an explanation of steps using proper terminology are provided in a separate document.1. What is the expected outcome for rolling a six-sided die using the discrete probability distribution table above?2. What is the probability of rolling an even number according to the discrete probability distribution table above?How does this compare to the theoretical probability of 0.5?Explain why you think there is a difference between the theoretical probability and the experimental probability you found.3. Create a binomial probability distribution based on the discrete probability distribution table above where a success is rolling an even number. Answer the following questions:How do you know this is a Binomial Probability Distribution? Explain by showing how this example fits all four properties of a Binomial Probability Distribution.Define n,p,q.What is the probability that you will roll exactly 12 even numbers?What is the probability that you will roll at least 12 even numbers?Find the expected number of even numbers that you will roll.Part Three - Continuous Probability DistributionDice are a common tool used in several board games. One board game which utilizes two dice is Monopoly. While the outcomes of rolling two dice in this game would be a discrete random variable, we are interested in looking at a continuous random variable associated with Monopoly and its respective probability.The time it takes to finish a game of Monopoly is normally distributed with a mean of 120 minutes and a standard deviation of 30 minutes. Using this premise, answer the following questions. Show all work for full credit. Calculations should be performed in Excel while answers including an explanation of steps using proper terminology are provided in a separate document.Explain why this is a continuous probability distribution instead of a discrete probability distribution.What is the probability that a game lasts less than 45 minutes?What is the probability that a game lasts more than 160 minutes?What is the z-score of a game that lasts exactly 105 minutes?
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