Heavy date analysis

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1) Using the Descriptive Statistics feature , of JASP or the Data Analysis ToolPak in Excel, generate numerical summary tables for all interval level or above variables in the dataset. Copy and paste the tables into this document. Ensure that the tables are APA formatted correctly

2) Determine the most representative measure of the center (mean or median) for EACH interval level and above variable in the dataset. Then determine the associated measure of spread (standard deviation or IQR) Type your responses in Table 1 below:

Table 1

Measures of Center and Spread for Variables in the Dataset

Variable	Measure of the Center	Measure of Spread	Rationale for Measure of Center Choice

3) Use the Correlation feature, in JASP or the Excel Data Analysis ToolPak, and generate ONE correlation table that contains correlations for all interval / ratio level variables. Copy and paste the correlation table here. Ensure it is APA formatted. Using complete sentences, write STATISTICAL interpretation AND an APPLIED interpretations of the values in the correlation table.

4) Generate a scatter plot for two of the interval/ ratio level variables (Your Choice) from the dataset. Copy and Paste the scatterplot here. Ensure that the chart is APA formatted.

5) Describe what the dot pattern, in the scatter plot from #4 above, reveals about the type of relation between the variables (linear or non-linear)

6) Using the Regression feature, in JASP or the Data Analysis ToolPak in Excel, generate the 3 Simple Regression output tables using one of your choice variables, made in #4 above, as the explanatory variable and the other as the response variable. Copy and paste all 3 tables here.

7) Using complete sentences, interpret the Multiple R and R Squared values. What do these values suggest about the relationship between the explanatory and response variables?

8) Using complete sentences, interpret the Significance of the simple regression model.

9) Using complete sentences, interpret the p-value in the Coefficient table for the explanatory variable. What does this suggest about the contribution of the explanatory variable to the predictability of the response variable?

10) Using the Regression feature, of JASP or the Data Analysis ToolPak in Excel, generate the Residual plot, Residual Histogram, and the Normality plot using the explanatory variable and the response variable you selected. Copy and paste charts here. Ensure that they are correctly APA formatted.

11) Using complete sentences, interpret the Residual plot. What does it suggest about the relationship between the explanatory and response variables?

12) Using complete sentences, interpret the Normality plot. What does it suggest about the response variable?

13) Using complete sentences, interpret the histogram. What does the shape of the histogram suggest about the feasibility of use of the Simple Regression table output results?

14) If it makes sense to do so, write out the potential Simple Regression equation. Be sure to use the both variable names when writing the equation. Referencing your evidences from above, discuss why it makes sense to run the analysis. If it does not make sense to write the equation, using complete sentences to explain why. Use the table below

Evidence	Rationale for or against running simple regression
Residual plot dot pattern
Normality Plot
Residual plot histogram