# Unit 9 Project

Unit 9 Project. Unit 9 Project.

Work through each of the following items to conduct an ANOVA F-test using the variables listed above for your unique IAT sample.
What is the explanatory variable, and what is the response variable?
What are the populations for the F-test?
Create side-by-side (or stacked) boxplots for the quantitative variable (IAT Score) grouped by your chosen categorical variable. Select the option to display the mean within the boxplots (directions) .Download the StatCrunch output window (your boxplots) and embed the .png file with your response.
Do the boxplots suggest that the samples come from populations with different means? Briefly explain.

Next, we need to create a table with these summary statistics: sample size, mean, and standard deviation for each of the populations you listed above. To do this, use StatCrunch to create a table of the indicated summary statistics for the quantitative variable (IAT Score) grouped by your chosen categorical variable. The summary statistics should be listed in the order given with no other statistics in your table.Copy the table in the StatCrunch output window and paste it into your response.
In your table, each group from your chosen categorical variable is labeled with a number. A reader will not understand what the number represents. Replace the numeric labels with descriptive words for each group of your selected categorical variable (see the Variables section above for your data set).

Determine whether conditions are met to use the ANOVA F-test. For each condition explain why the condition is met or not met.

Conducting the ANOVA F-test at the 5% significance level:If conditions are met, use StatCrunch to conduct the ANOVA F-test (copy and paste the contents of the StatCrunch output window into your response). Identify the F-statistic and the P-value. Then state your conclusion in context.
If conditions are not met for your selected categorical variable, start over and use the list of categorical variables provided in the Variables section above to select a different categorical variable for which conditions are met.
If conditions are not met for all categorical variables listed above for your data set, contact me.

done
Seen
few seconds ago[supanova_question]

## Statistics Question

Use the Sun Coast Remediation data set to conduct a correlation
analysis, simple regression analysis, and multiple regression analysis
using the correlation tab, simple regression tab, and multiple
regression tab respectively. The statistical output tables should be cut
and pasted from Excel directly into the final project document. For the
regression hypotheses, display and discuss the predictive regression
equations if the models are statistically significant. Delete
instructions and examples highlighted in yellow before submitting this
assignment.
Correlation: Hypothesis Testing
Restate the hypotheses from Unit II here.
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1: There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
Using an alpha of .05, the results indicate a p value of
.023 < .05. Therefore, the null hypothesis is rejected, and the
alternative hypothesis is accepted that there is a statistically
significant relationship between height and weight.
Note: Excel data analysis Toolpak does not automatically calculate the p
value when using the correlation function. As a workaround, the data
should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function.
Simple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho2:
Ha2:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation.
Multiple Regression: Hypothesis Testing
Restate the hypotheses from Unit II here.
Ho3:
Ha3:
Enter data output results from Excel Toolpak here.
Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include multiple R, R squared, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, and the regression model as an equation with explanation.
References
Include references here using hanging indentations. Remember to remove this example.
Creswell, J. W., [supanova_question]

## This is an introductory class to the language R Studio, so make sure that the code is not advanced.

Unit 9 Project skepticismgive-a-new-title/”>Statistics Assignment Help This is an introductory class to the language R Studio, so make sure that the code is not advanced. I will upload all the documents given to us. When giving me the final code, I need you to submit a .rmd, as well as knit the .rmd file into a pdf and attach that as well. If there are any changes that I need to do on my part aka directory changes or anything else to make it seem like I have completed it on my computer, let me know! Don’t forget to knit the code into pdf. Also, complete all the work on the hw3.rmd file I will attach.

Additionally, I will be attaching all the class lecture scriipts that you will need to have the context to solve these problems. If you need any more lecture scriipts just give me context as to what they are about and I will send them over.[supanova_question]

## Discussion for stats

Describe a potential example of an “independent samples t-tests” that could be conducted within the social sciences, and list what you believe the outcome of the research would be for this study. No data or calculations are necessary whatsoever, but you should describe why you developed your chosen hypothesis (e.g., based on your own understanding of current research, real world observations, a wild guess, etc.).
To receive full credit, this first section must be at least 100 words. Once you submit this post, you will then have access to everyone else’s posts, at which point you must then respond to at least one other student by adding to their discussion, asking them a question, or reacting to their post in a meaningful way. For instance, maybe you disagree with their hypotheses and you’d like to offer an alternative perspective.

done
Seen

Oct 30th, 2021[supanova_question]

https://anyessayhelp.com/ This is an introductory class to the language R Studio, so make sure that the code is not advanced. I will upload all the documents given to us. When giving me the final code, I need you to submit a .rmd, as well as knit the .rmd file into a pdf and attach that as well. If there are any changes that I need to do on my part aka directory changes or anything else to make it seem like I have completed it on my computer, let me know! Don’t forget to knit the code into pdf. Also, complete all the work on the hw3.rmd file I will attach.

Additionally, I will be attaching all the class lecture scriipts that you will need to have the context to solve these problems. If you need any more lecture scriipts just give me context as to what they are about and I will send them over.[supanova_question]