Lab Assignment #3

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San Diego State University *

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490A

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Statistics

Date

Apr 3, 2024

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docx

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Uploaded by BrigadierBatMaster902

PH490A Lab Assignment #3 Learning Objectives for Lab Assignment #3 ● Construct and analyze crosstab for 2 variables ● Conduct a chi-square test of independence for two variables and interpret the output This lab you will practice analyzing bivariate categorical data (two nominal or ordinal variables at a time) by constructing crosstabs (crosstabulation tables). You will also conduct a chi-square test of independence (“chi-square test”) to examine the statistical relationship between two variables and interpret the results of the test. For this lab, we will use 2019 Monitoring the Future Survey data from 12 th graders in U.S. schools. You downloaded this dataset previously. If you have not downloaded the dataset yet, please refer to the previous information for instructions on how to access and download the dataset. Please answer each of the following questions in full. For some you will type your answers (please use full sentences with proper grammar). For others, you will copy screenshots or provide key information from your SPSS output. Please ALSO attach or submit your SPSS output with every assignment! You will lose 5 points if the SPSS output is not uploaded with the assignment submission. These assignments should be completed individually, and each person must submit an independent lab assignment. You are encouraged to discuss the labs with your peers/group, but each student should write up their answers independently . Part 1: Setting up Your Data Step 1: Open the core survey dataset file (“DS001”) and “Save as” a new file with the name “DS001_Lab3”. Open the codebook (PDF). Step 2: Identify the following two variables in the dataset: (A) Political Beliefs and (B) Race. Review the name/code, survey question, and response options for each of these variables. Use the PDF of the codebook to help you; starting on page 40 of the codebook and using the Find feature on your laptop will help find the appropriate variables. ● Political Beliefs: How would you describe your political beliefs? ● Race : How do you describe yourself? (Select one or more responses.) Step 3: Check your variables. Run the SPSS codebook to examine the 3 variables. Analyze < Reports < Codebook < Select variables. Step 4: Rename the variable for Race to “Race” and Political Beliefs to “Political_Beliefs” and change the measurement (ordinal, nominal, interval/ratio) if necessary. Step 5: Check your variables. Re-Run the codebook with the new names for the 2 variables. Analyze < Reports < Codebook < Select variables. QUESTION 1 (1 pt) : What proportion of participants reported that they are “Very Conservative”? What percentage reported that they are “Radical”?

PH490A Part 2 : Bivariate Descriptive Analysis Step 6: Recode “Political Beliefs” to be dichotomous (two categories) and add “None/Don’t Know with missing”: ● New variable name = Political_Beliefs_Di ● Category 1 = Very Conservative, Conservative, and Moderate ● Category 2 = Liberal, Very Liberal, and Radical ● Set “None/Don’t know” = Missing ● SYS Missing= SYS Missing Transform < Recode Into Different Variables Output Variable < Name = Political_Beliefs_Di; Label = Political Beliefs Binary (“Change”) Old and New Values < Old Value = 8, New Value = SYS Missing < Add < Old value, Range = 1 – 3, New Value = 1 < Add < Old value, Range = 4 – 6, New Value = 2 < Add < Old value SYS Missing, New value = SYS Missing, < Add < Continue < OK Step 7: In variable view, update the measurement of the new variable to the appropriate measurement type (nominal, ordinal, interval/ratio) and name the values. ● Value 1 = Conservative/Moderate ● Value 2 = Liberal/Radical Variable View < Measure = Nominal Values < Value 1 = Conservative/Moderate < Add < Value 2 = Liberal/Radical < Add < OK Step 8: Check your new political beliefs variable (dichotomous recode) against the original political beliefs variable using the codebook feature to ensure your recoding looks right (do the categories add up as you intended)? Analyze < Reports < Codebook QUESTION 2 (2 pts) : For your new variable, what proportion of participants identified as Conservative/Moderate? What proportion of high school seniors had missing data on this question (based on your new categorization)? Copy and paste a screenshot of your codebook output for your new and old political beliefs variables. Step 9: Create a crosstab of the variables Political_Beliefs_Di (Row) and Race (Column) that includes the column percents. Analyze < Descriptive Statistics < Crosstabs < Row = Political_Beliefs_Di < Column = Race < Cells < Percentages < Select “Column” (leave everything else the same) < Continue < OK QUESTION 3 (1pt) : How many Black high school seniors are Liberal/Radical? QUESTION 4 (3 pts) : Among high school seniors who are Hispanic/Latinx, what percentage are Conservative/Moderate (column-percent)? What corresponding proportion was used to calculate this percentage (f/n x 100)? Step 10: Re-create the crosstab from Step 9 and add row percents (do not remove column percents) .

PH490A Analyze < Descriptive Statistics < Crosstabs < Row = Political_Beliefs_Di < Column = Race < Cells < Percentages < Select “Column” and “Row” (leave everything else the same) < Continue < OK QUESTION 5 (1 pt) : Copy and paste a screenshot of your crosstab of Political_Beliefs_Di X Race that includes column and row percentages. QUESTION 6 (3 pts) : Among high school seniors who are Liberal/Radical, what proportion are Hispanic/Latinx (row-percent)? What corresponding proportion was used to calculate this percentage (f/n x 100)? QUESTION 7 (2 pts) : Among white high school seniors – what percentage are Conservative/Moderate versus Liberal/Radical? Compare that to the political beliefs among high school seniors who are Black – what percentage or proportion are Conservative/Moderate versus Liberal/Radical? Part 3: Chi-Square Test of Independence Step 11 : Re-create the crosstab from Step 10. Remove the Column and Row percents. Apply the Chi- Square test of independence to examine the statistical relationship between your race and political beliefs dichotomy variables. Analyze < Descriptive Statistics < Crosstabs < Row = Political_Beliefs_Di < Column = Race < Cells < Percentages < Unselect “Column” and “Row” (leave everything else the same) < Continue < Statistics < Select “Chi-square” (leave everything else as is/unchecked) < Continue < OK QUESTION 8 (3 pts) : What is the research question and the null and alternative hypothesis we are testing by applying the Chi-Square test of Independence to these two variables? QUESTION 9 (1 pt) : Copy and paste the “Chi-Square Tests” table from your output. QUESTION 10 (2 pts) : What is the χ 2 ❑ (chi-square) value and level of significance (p-value) for the “Pearson Chi-Square”? QUESTION 11 (4 pts) : Based on an alpha level of 0.05, what can we conclude about the relationship between 12 th graders’ political beliefs and their race? Note: Statistical significance is determined by citing an alpha level, or the probability of rejecting the null hypothesis when the null hypothesis is actually true. In public health and social science research, we often use an alpha of 0.05 (5%) . QUESTION 12 (2 pts) : Based on our results, can we determine why there is a relationship between political beliefs and race? Why or why not?

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