This is a statistical Inference project. It requires Janovi to work the spreadsheet provided. I have the file but it is not a format that I am able to upload on here. Anyone still able to help??
Project Details
A. Select one of the datasets provided.
B. Create two hypotheses.
1. One must be able to be tested using a dependent means or paired samples t-test.
2. One must be able to be tested using an independent means and independent samples t-test.
C. Describe the variables used in your hypotheses.
1. Describe the variables in words.
2. Describe the variables numerically. For example, present measures of central tendency and variability (when appropriate) for the major variables.
3. Describe the variables graphically.
4. You should interpret these and not simply present the numbers.
5. Report demographic information of the sample, such as average age, percent of males and females.
6. Create a least one box plot, one histogram, and one frequency table. You should interpret these and not simply present the graphs/tables.
D. Test your hypotheses using the appropriate statistical procedure in Jamovi. For each hypothesis write a paragraph that states the statistics you ran and why. See the example below for details.
1. Write the results of what you found in APA style and provide relevant output at the end of the report.
2. State whether your results support or fail to support your hypothesis.
E. Create a report (approximately 2 – 5 pages) that combines what you completed and found in main bullet points B – D.
Example Write-up
Here is an example of what a write-up for a Chi-Square statistic might look like. Although this is not a template, this should help in formulating this report.
It was hypothesized that the number of people in my sample that liked cheese pizza would be greater than the number who liked anchovy pizza. To test this, a Chi—Square goodness of fit test was used. This test compares the observed frequency of categories in a single nominal/categorical variable, which is appropriate for comparing the frequency of pizza choice (the nominal/categorical variable) for the options of cheese or anchovy (the categories). A Chi-square goodness of fit test compared the frequency of cheese and anchovy pizza preference. We hypothesized that both would occur with equal frequency. A significant deviation from hypothesized values was found, χ2(1) = 25.92, p < .001. The observed frequency of preference for cheese (43) and anchovy (7) were significantly different from the expected frequency of each (25). This difference represents a large effect, ɸ = .72. These findings support our hypothesis, as significantly more people in our sample preferred cheese pizza (43) compared to anchovy pizza (7).
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