Asking chatgpt to propose a survey questionnaire: a note for Housing Studies students

Asking chatgpt (accessed via poe.com) to propose a survey questionnaire: a note for Housing Studies students

My request is as follows: "I am a part-time Housing Studies student. I am working on my Research Methods assignment. My research topic is on "An assessment of how the economic and demographic trends affect the home ownership plan of the millennials in Hong Kong". I would like to conduct a questionnaire survey with my friends. The questionnaire should have about 20 questions, all in the forms of 5-point rating scale or option ticking only. Some of the questions should be related to the personal profile of the respondent, some should be related to the respondent's view on how the economic and demographic trends affect the housing market and, finally, some questions should be related to the respondent's home ownership plan. Based on these requirements, could you propose a survey questionnaire to me? Many tks."

The response from chatgpt: "Sure! Here’s a proposed questionnaire for your research on how economic and demographic trends affect the home ownership plans of millennials in Hong Kong. The questions are structured to fit a 5-point rating scale (1 = Strongly Disagree, 5 = Strongly Agree) or option ticking.

Questionnaire

Section 1: Personal Profile

Age:

 18-24

 25-30

 31-35

 36-40

 41 or older

Gender:

 Male

 Female

 Non-binary

 Prefer not to say

Current Employment Status:

 Employed full-time

 Employed part-time

 Self-employed

 Unemployed

 Student

Annual Income:

 Below HKD 200,000

 HKD 200,000 - 400,000

 HKD 400,000 - 600,000

 HKD 600,000 - 800,000

 Above HKD 800,000

Section 2: Views on Economic and Demographic Trends

I believe that rising property prices in Hong Kong are a barrier to home ownership for millennials.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I think the current economic situation in Hong Kong influences my decision to buy a home.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I feel that job stability is a crucial factor in planning for home ownership.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I believe that demographic changes (e.g., aging population) will impact the housing market in Hong Kong.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I think government policies significantly affect housing affordability for millennials.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I am concerned about the availability of affordable housing options in Hong Kong.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

Section 3: Home Ownership Plans

I plan to own a home within the next 5 years.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I have already started saving for a down payment on a home.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I would consider buying a property outside of Hong Kong if prices remain high.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I think renting is a better option than buying right now.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I believe that my financial situation will improve, making home ownership more feasible in the future.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I think my social network influences my views on home ownership.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I feel confident in my knowledge of the home buying process.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I believe that owning a home is a critical part of financial security.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I am willing to compromise on the size or location of a home to achieve ownership.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

I believe that millennials in Hong Kong face unique challenges in achieving home ownership.

 1 (Strongly Disagree)

 2

 3

 4

 5 (Strongly Agree)

Conclusion

Thank you for participating in this survey! Your responses will greatly assist in understanding the factors affecting home ownership plans among millennials in Hong Kong."

My request 2: "I also intend to use Excel to analyze the survey data. Specifically, I intend to (i) produce 3 graphs based on the survey data, (ii) produce 5 cross-tabulation tables using Excel pivot table (focusing on the value variables from the 5 questionnaire questions 15, 17, 18, 19, and 20; in this case, 1 table covers one of these question value), and (iii) produce a multiple regression analysis using questionnaire questions 11, "I plan to own a home within the next 5 years" (as the Y variable). Could you propose a more detailed quantitative data analysis design with Excel for me?"

The response from chatgpt is : "Certainly! Here’s a detailed plan for analyzing your survey data using Excel, focusing on graphs, cross-tabulation tables, and multiple regression analysis.

Quantitative Data Analysis Design in Excel

1. Data Entry

Create an Excel spreadsheet to input your survey data.

Each row should represent a respondent, and each column should represent a question from your questionnaire.

2. Producing Graphs

You need to generate three graphs based on the survey data. Here are some suggestions:

Graph 1: Respondent Age Distribution

Type: Bar Chart

Data: Count the number of respondents in each age category from Question 1.

Graph 2: Home Ownership Plan Intentions

Type: Pie Chart

Data: Visualize the distribution of responses for Question 11 ("I plan to own a home within the next 5 years") by counting the number of responses for each rating (1 to 5).

Graph 3: Economic Concerns

Type: Line Chart

Data: Plot the average responses for Questions 6, 10, and 20 to show how views on economic and demographic trends correlate with home ownership plans.

3. Cross-Tabulation Tables

Use Excel Pivot Tables to create five cross-tabulation tables focusing on questions 15, 17, 18, 19, and 20. Here's how to do it:

Table for Question 15: Financial Situation Improvement

Rows: Age categories (Question 1)

Values: Average response for Question 15

Table for Question 17: Knowledge of Home Buying

Rows: Gender (Question 2)

Values: Average response for Question 17

Table for Question 18: Home Ownership and Financial Security

Rows: Employment Status (Question 3)

Values: Average response for Question 18

Table for Question 19: Willingness to Compromise

Rows: Income Categories (Question 4)

Values: Average response for Question 19

Table for Question 20: Unique Challenges for Millennials

Rows: Employment Status (Question 3)

Values: Average response for Question 20

4. Multiple Regression Analysis

Conduct a multiple regression analysis using Question 11 as the dependent variable (Y variable). Here’s how:

Prepare Data:

Ensure that all relevant independent variables (X variables) are included in your dataset. You can use Questions 15, 17, 18, 19, and 20 as the independent variables.

Perform Regression Analysis:

Go to the "Data" tab in Excel.

Click on "Data Analysis" (if not available, you may need to add the Analysis ToolPak via Excel Options).

Select "Regression" from the list.

Set the Input Y Range to the data for Question 11.

Set the Input X Range to the data for Questions 15, 17, 18, 19, and 20.

Choose an output range for the regression results.

Interpret Results:

Look for the R-squared value to understand the model fit.

Analyze the coefficients for each independent variable to determine their impact on the home ownership plan.

Conclusion

By following this design, you’ll be able to effectively analyze your survey data in Excel. The graphs will provide visual insights, the cross-tabulation tables will help explore relationships between variables, and the multiple regression analysis will offer a deeper understanding of factors influencing home ownership plans among millennials in Hong Kong."

My request 3: "Tks. For the pivot table analysis, could you propose cross-tabulation tables with 1 column dimension and 1 row dimension in order to produce a kind of multi-dimensional data analysis?"

The response from chatgpt is: "Certainly! Below are proposed cross-tabulation tables for your pivot table analysis, structured with one column dimension and one row dimension to facilitate multi-dimensional data analysis. Each table focuses on one of the specified questions (15, 17, 18, 19, and 20) and provides insights based on different demographic variables.

Proposed Cross-Tabulation Tables

1. Table for Question 15: Financial Situation Improvement

Row Dimension: Age Categories (from Question 1)

Column Dimension: Average response for Question 15 (1-5 scale)

Purpose: To analyze how perceptions of financial improvement differ across age groups.

Age Group Average Response for Q15 (1-5)

18-24

25-30

31-35

36-40

41 or older

2. Table for Question 17: Knowledge of Home Buying

Row Dimension: Gender (from Question 2)

Column Dimension: Average response for Question 17 (1-5 scale)

Purpose: To compare perceived knowledge of the home buying process between genders.

Gender Average Response for Q17 (1-5)

Male

Female

Non-binary

Prefer not to say

3. Table for Question 18: Home Ownership and Financial Security

Row Dimension: Employment Status (from Question 3)

Column Dimension: Average response for Question 18 (1-5 scale)

Purpose: To see how views on home ownership and financial security vary by employment status.

Employment Status Average Response for Q18 (1-5)

Employed full-time

Employed part-time

Self-employed

Unemployed

Student

4. Table for Question 19: Willingness to Compromise

Row Dimension: Income Categories (from Question 4)

Column Dimension: Average response for Question 19 (1-5 scale)

Purpose: To analyze willingness to compromise based on income levels.

Income Category Average Response for Q19 (1-5)

Below HKD 200,000

HKD 200,000 - 400,000

HKD 400,000 - 600,000

HKD 600,000 - 800,000

Above HKD 800,000

5. Table for Question 20: Unique Challenges for Millennials

Row Dimension: Employment Status (from Question 3)

Column Dimension: Average response for Question 20 (1-5 scale)

Purpose: To evaluate perceptions of the unique challenges faced by millennials in relation to their employment status.

Employment Status Average Response for Q20 (1-5)

Employed full-time

Employed part-time

Self-employed

Unemployed

Student

Conclusion

These cross-tabulation tables will allow you to conduct a multi-dimensional analysis, helping to uncover relationships between demographic factors and perceptions regarding financial situations, knowledge of home buying, and attitudes toward home ownership. This approach will enhance your understanding of how various factors impact millennials' home ownership plans in Hong Kong."

Further reading: interview design: the inductive approach vs deductive approach

Reference: a collection of blog notes on using chatgpt for research purpose.