# HBC203: (Statistics and Data Analysis for the Social and Behavioural Sciences)

**Module / Subject / School**:

HBC203: Statistics and Data Analysis for the Social and Behavioural Sciences

Singapore University of Social Sciences (SUSS)

**Requirements:Â **

**Question 1 (20 marks)**

Ravi, a communications researcher, wants to find out if Singaporean parentsâ€™ concern about their childrenâ€™s exposure to inappropriate content on social media changed significantly one year after the outbreak of the COVID-19 pandemic (i.e., 2021) compared to before (i.e., 2018). Out of the 315 parents he surveyed in 2021, 46.03% were extremely concerned, 26.03% were somewhat concerned, and 27.94% were a little or not at all concerned. Out of the 436 parents he surveyed in 2018, 40.14% were extremely concerned, 34.63% were somewhat concerned, and 25.23% were a little or not at all concerned.

Identify the most appropriate statistical test to conduct to find out whether if Singaporean parentsâ€™ concern about their childrenâ€™s exposure to inappropriate content on social media changed significantly from 2018 to 2021.

Explain why this is the most appropriate statistical test by providing two reasons in the context of this study. Then, assuming all the assumptions of the statistical test you identified are met, analyse the data using jamovi. Show the jamovi spreadsheet by taking a screenshot of the spreadsheet (i.e., what you see when you click the DATA tab) and pasting it in your answer.

**What we score:**

79%

**Our Writer’s CommentÂ **

### Step 1: Choosing the Most Appropriate Statistical Test

1. Recognize the type of data:

In this case, Ravi is comparing the distribution of parental concerns (in three categories: extremely concerned, somewhat concerned, and a little/not concerned) between two different time periods (2018 vs. 2021). Since the concern levels are categorical data and youâ€™re interested in whether thereâ€™s a significant change in the distribution of these categories across two different years, the Chi-square test of independence is the most appropriate statistical test.

2. Two reasons why the Chi-square test is appropriate:

- Reason 1: The Chi-square test of independence is used when you are working with two categorical variables(in this case, the year of the survey and the level of concern). It tests whether the distribution of concern levels in 2021 is significantly different from the distribution in 2018.
- Reason 2: Both sample sizes (315 in 2021 and 436 in 2018) are large enough to meet the assumptions of the Chi-square test, which require that the expected frequency in each category be at least 5. This ensures that the Chi-square test can give reliable results.

### Step 2: Analyzing the Data Using jamovi

1. Enter the data in jamovi:

Before you can run the Chi-square test, youâ€™ll need to enter your data correctly into jamovi. The data for this test should include:

- One variable for the year (2018 or 2021),
- One variable for concern level (extremely concerned, somewhat concerned, a little/not concerned).

Make sure the data is formatted properly, with each row representing a participant and their corresponding year and concern level.

2. Take a screenshot of the jamovi spreadsheet:

Once your data is entered, go to the DATA tab in jamovi and take a screenshot of the spreadsheet. Make sure that your data is clearly formatted and ready for analysis. This will show the marker that you’ve input the data correctly.

### Step 3: Running the Chi-square Test in jamovi

1. Run the Chi-square test:

In jamovi, go to the Frequencies module and choose the Chi-square test of independence. Select the two variables (year and concern level) and let jamovi run the analysis.

2. Copy the output:

After running the test, copy and paste the output into your answer. This output will include the Chi-square statistic (Ď‡Â˛), degrees of freedom (df), and the p-value.

### Step 4: Interpreting the Results

1. Report the results in APA format:

Using an alpha level of .05, interpret the results in APA format. For example, if the p-value is less than .05, you would report that there is a statistically significant difference in concern levels between 2018 and 2021.

2. Provide a plausible explanation for the results:

Now, think about why the concerns may have shifted from 2018 to 2021. A plausible explanation could be that the COVID-19 pandemic caused parents to become more aware of the potential risks of social media as children spent more time online during lockdowns and restrictions.

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