Nov 11, 2024
NavAI is an AI data analytics and forecasting tool powered by LLM that allows you to interact with your data.
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NavAI is an AI data analytics and forecasting tool powered by LLM that allows you to interact with your data.
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Chi Square Test of Independence
1. Code： FILENAME REFFILE '/home/liwenzhang08220/_cf16dab6c94262cc58a6bd4e0f753e56_nesarc_pds.csv'; PROC IMPORT DATAFILE=REFFILE DBMS=CSV OUT=WORK.IMPORT1; GETNAMES=YES; RUN; PROC CONTENTS DATA=WORK.IMPORT1; RUN; DATA WORK.IMPORT1; SET WORK.IMPORT1; IF S3BQ1A3=9 THEN S3BQ1A3=.; RUN; PROC FREQ; TABLES S3BQ1A3*REGION/CHISQ; RUN; DATA WORK.IMPORT1; SET WORK.IMPORT1; IF REGION=1 OR REGION=2; PROC FREQ; TABLES S3BQ1A3*REGION/CHISQ; RUN;
2. Graph and Interpretation
H0: There is no relationship between drug use ever used opioids and regions
Ha: There is a relationship between drug use ever used opioids and regions Result: X2=96.87,3 df, p<0.001. reject H0 and accept Ha. When examining the association between drug use ever used opioids (categorical response) and regions (categorical explanatory), a chi-square test of independence revealed that there is a relationship between drug use ever used opioids and different regions.
2. Interpretation for post hoc Chi-Square Test result; Since there are 4 different regions, I just show one comparison between region 1 and 2. Post hoc comparisons of drug used in region 1 (Northeast) and 2 (Mideast) revealed that 3.30% people used the drug at Northeast and 96.70% people used the drug at Mideast. In addition, there is a significant difference in drug use (OPIOIDS) between the Northeast and Mideast (X2=18.78, df1, p<0.001).
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Data Analysis Week-4 Assignment
Dataset:
The dataset contains variables like life satisfaction score, food satisfaction score, income.
Aim:
To check the moderating effect of the income variable in the association between general life satisfaction and food satisfaction.
Python code Syntax:
Python Output:
association between Food satisfaction and Life satisfaction for LOW income persons (-0.16666666666666666, 0.7887799817897356)
association between Food satisfaction and Life satisfaction for MIDDLE income persons (0.9707253433941508, 0.15442095831126684)
association between Food satisfaction and Life satisfaction for HIGH income persons (-0.37241359182061873, 0.2593587449924706)

Interpretation:
The income variable does not have a relationship between the association between life satisfaction score and food satisfaction score.
As evident in the graph, the correlation value is not significant as p-value in all the income level is greater than 0.05(level of significance -0.05).