Problem 3: Market Research for a New Product Launch Context: A company is planning to launch a new electronic gadget and conducts extensive market research to understand consumer preferences and predict sales performance. Data Collection: A survey is distributed to 1,000 potential customers, collecting the following information: • Age: Numerical value. • Income Level: Categorical variable (Low, Medium, High). • Preferred Features: Multiple selections (e.g., Battery Life, Design, Price, Brand Reputation). . Purchase Intention: Likert scale (1-5, where 1 = Very Unlikely, 5 = Very Likely). • Previous Purchases: Number of similar gadgets purchased in the past year. Tasks: 1. Data Visualization: . Create a histogram showing the distribution of ages of the survey respondents. • Develop a bar graph illustrating the frequency of each income level category. . Construct a stacked bar chart displaying the preferred features across different income levels. Plot a histogram for purchase intentions scores. 2. Statistical Analysis: Calculate the mean and median purchase intention scores overall and segmented by income level. Perform a chi-square test to examine the association between income level and preferred features. • Analyze the relationship between previous purchases and purchase intention using regression analysis. 3. Advanced Visualization: . Create a scatter plot with income level (numerical encoding) on the x-axis and purchase intention on the y-axis, differentiating points by preferred feature. Develop a heatmap to show the correlation matrix between all numerical variables (Age, Purchase Intention, Previous Purchases).

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section: Chapter Questions

Problem 9SGR

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Transcribed Image Text:Problem 3: Market Research for a New Product Launch Context: A company is planning to launch a new electronic gadget and conducts extensive market research to understand consumer preferences and predict sales performance. Data Collection: A survey is distributed to 1,000 potential customers, collecting the following information: • Age: Numerical value. • Income Level: Categorical variable (Low, Medium, High). • Preferred Features: Multiple selections (e.g., Battery Life, Design, Price, Brand Reputation). . Purchase Intention: Likert scale (1-5, where 1 = Very Unlikely, 5 = Very Likely). • Previous Purchases: Number of similar gadgets purchased in the past year. Tasks: 1. Data Visualization: . Create a histogram showing the distribution of ages of the survey respondents. • Develop a bar graph illustrating the frequency of each income level category. . Construct a stacked bar chart displaying the preferred features across different income levels. Plot a histogram for purchase intentions scores. 2. Statistical Analysis: Calculate the mean and median purchase intention scores overall and segmented by income level. Perform a chi-square test to examine the association between income level and preferred features. • Analyze the relationship between previous purchases and purchase intention using regression analysis. 3. Advanced Visualization: . Create a scatter plot with income level (numerical encoding) on the x-axis and purchase intention on the y-axis, differentiating points by preferred feature. Develop a heatmap to show the correlation matrix between all numerical variables (Age, Purchase Intention, Previous Purchases).

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