learning data analysis skills using traditional statistical tools alongside AI tools to replicate compare results

Overview

This assignment focuses on learning data analysis skills using traditional statistical tools (SPSS) alongside AI tools (e.g., ChatGPT) to replicate and compare results. By completing this assignment, you will explore:

1. Hypothesis testing using traditional statistical packages.
2. The capabilities and limitations of AI tools for data analysis.

3.Practical insights and implications for marketing research.

Instructions

A pilot survey was conducted with 30 respondents to examine Internet usage for personal reasons. The dataset, titled internet_usage.sav, contains the following variables:

• •Gender (1 = male, 2 = female)
• •Familiarity with the Internet (1 = very unfamiliar, 7 = very familiar)
• •Internet usage in hours per week
• •Attitudes toward the Internet and technology (measured on 7-point scales)

Online shopping and banking behaviors (1 = yes, 2 = no)

Tip: Feel free to reference materials in the Intro to SPSS folder (Content) for guidance on conducting these analyses. You may also ask ChatGPT if you get stuck.

Part A: Data Preparation

1.Construct a Codebook:

• •Include: Name (e.g., "Gender"), Description (e.g., "Respondent's gender"), Type (categorical or continuous), and Values (for categorical variables, list all possible values, e.g., 1 = Male, 2 = Female)

Create a table summarizing all variables.

1. Descriptive Statistics and Frequency Distributions:
2. Data Cleaning:

• •Calculate descriptive statistics (mean, median, standard deviation) for all continuous variables.
• •Generate frequency distributions for categorical variables.

Visualize data using histograms for continuous variables.

• •Identify anomalies or outliers and document them.
• •Use mean substitution for missing values.

Recalculate descriptive statistics for cleaned data and note changes.

Part B: Data Analysis

1.Traditional Statistical Analysis:

Conduct the following tests using SPSS:

• •Cross-Tabulation and Chi-Square Test: Recode Internet usage into light (≤ 5 hours) and heavy (> 5 hours). Perform a Chi-square test to evaluate gender differences in usage levels.
• •One-Sample t-Test: Test if the mean familiarity with the Internet exceeds 4.0.
• •Independent-Samples t-Test: Test if familiarity differs between those who shop online and those who don't. Test if familiarity differs between those who bank online and those who don't.
• •Paired-Samples t-Test: Test if attitudes toward the Internet differ from attitudes toward technology.

Document the results, including p-values, test statistics, and interpretations.

1. AI-Assisted Replication:
2. Comparison of Results:

• •Use ChatGPT (or another AI tool) to replicate the analyses performed in the previous step.
• •Provide the following to the AI: a summary of the data variables and descriptions, and instructions for each statistical test.

Document the AI-generated results and compare them with the results from traditional tools.

• •Highlight any similarities or discrepancies between traditional tools and AI results.

Discuss potential reasons for discrepancies, including data interpretation, rounding differences, or AI limitations.

Part C: Practical Implications and Reflection

Interpret Findings: Summarize practical implications for marketing strategies based on your analysis. Example: How could insights into familiarity with the Internet influence online marketing campaigns?

• •AI vs. Traditional Tools: Reflect on the benefits and limitations of using AI tools for data analysis compared to traditional statistical packages. Example: Did AI simplify any part of the analysis or introduce unexpected challenges?

Reflection on Limitations: Discuss potential limitations of the dataset, analysis methods, or AI replication. How could these limitations impact your findings?

Deliverables

Submit a report (3-5 pages) including:

• •Codebook: Detailed descriptions of variables.
• •Descriptive Statistics: Pre- and post-cleaning results.
• •Statistical Test Results: Output from SPSS and ChatGPT comparisons.
• •Interpretations: Practical implications of findings.

AI Reflection: A summary of the AI's performance in replicating the analysis.