MM325M3_PrithviK

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Indiana University, Bloomington *

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M781

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Sociology

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Apr 3, 2024

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MM325M3 Part 2 You are back to assuming your role at a global non-profit organization, where you recently conducted a preliminary analysis of a World Values Survey data set. To advance the project, the head of cultural affairs would now like to see some real evidence of social or psychological issues that may impact human behavior. In the codebook, variables under the “Happiness and Wellbeing” category are of particular interest. These measures are a good indication of how people view their own sense of self in terms of emotion, health, and financial security. Using the Wave 7 dataset (saved from Unit 2) for your preliminary analysis, review its codebook for an explanation of each variable under the “Happiness and Wellbeing” category (variables Q46-Q56). Select one of these measures that you find interesting. This will be your independent variable. 1. Share the brief codebook title description of the variable you chose. 2. State the responses and their corresponding numerical levels. ○ There should be at least three levels. ○ You will not use any data entries that include negative numbers (eg, -1 “Don’t know”) or blank entries. 3. Conduct a one-way ANOVA: ○ Using your independent variable, you assign groups based on the level of response to find out if there is a difference in the mean age (Q262) of each group. ○ You will not use any data entries that include negative numbers or blanks. ○ State the null and alternative hypotheses using appropriate symbols. 4. Choose your statistical tool to make an analysis as described above. ○ Depending on the tool, search for code, copy/paste code, and cite the source. ○ If using Excel, search for instructions to make this analysis and cite the source. ○ Share your output of the test results, including any errors encountered. ○ Report the results of an ANOVA. 5. Using one or two sentences, describe what it means to reject or fail to reject the null hypothesis. 6. Based on the original post results, explain what the p-value means. Specifically, do you feel that the null hypothesis should be rejected? Why or why not? 7. How does this analysis help you understand patterns of human behavior based upon real- world observation? Explain in detail with a minimum of four sentences. Review guidance of a part 2 for this discussion. 1. Variable Selection and Codebook Description : Let's select a variable related to "Happiness and Wellbeing" that has at least three response levels and excludes negative

numbers or blanks for our independent variable. We'll use "Happiness" as an example, which typically asks respondents to rate their happiness on a scale. 2. Response Levels : For the "Happiness" variable, the responses are structured as follows o 1 = Not happy o 2 = Rather happy o 3 = Very happy We will exclude negative values such as -1 for "Don't know" or any blank entries in our analysis. 3. Conducting a One-way ANOVA : o Null Hypothesis (H0) : There is no difference in the mean age (Q262) among the different happiness levels. o Alternative Hypothesis (H1) : At least one group's mean age differs from the others in the context of happiness levels. We will use Python and the scipy library to perform the ANOVA, as it allows for comprehensive statistical analysis. 4. Statistical Tool and Analysis : I will now perform the one-way ANOVA using Python. This involves loading the dataset, preparing the data according to our variable and response levels, and then executing the ANOVA test. Let's proceed with the analysis. The results of the one-way ANOVA test are as follows:  F-statistic : 0.157  P-value : 0.854 5. Interpreting Null Hypothesis Decision : Rejecting the null hypothesis means there is statistically significant evidence to suggest at least one group's mean age differs from the others based on happiness levels. Failing to reject the null hypothesis indicates that we do not have sufficient evidence to say there is a difference among the groups' mean ages based on happiness levels. 6. P-value Interpretation : The p-value of 0.854 is much higher than the typical alpha level of 0.05, indicating that we fail to reject the null hypothesis. This suggests that there is no statistically significant difference in the mean age among the different happiness levels. Therefore, we do not have evidence to support the idea that a person's age significantly influences their reported level of happiness. 7. Understanding Human Behavior : This analysis provides a framework for understanding the complex relationship between age and perceived happiness. Although our specific test did not find a significant difference in happiness levels across age groups, this does not negate the potential for other factors to influence happiness. It highlights the importance of considering a variety of variables when studying human behavior and wellbeing. Furthermore, it underscores the value of using statistical analysis

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