Josh Batteer Project 5 Write-Up

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University of South Carolina *

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Statistics

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Feb 20, 2024

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pdf

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Josh Batteer Project 5 I decided to come to two conclusions to try and see if there is correlation with the responses of my survey. My first question was whether or not the respondent’s household income is statistically significant to the respondent’s interest in the solar powered charging phone case. My next question was whether or not the respondent’s gender is statistically significant to the respondent’s interest in the solar powered charging phone case. I decided to run a simple linear regression to determine whether these mix of variables were statistically significant with each other. Here is my simple linear regression for household income based on the interest in the product: > reg = lm(Q15 ~ Q1, data = Josh_Batteer_Project_4) Results: Residuals: Min 1Q Median 3Q Max -4.3172 -0.3172 0.6828 0.6828 1.3595 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 4.4150 0.7590 5.817 1.35e-06 *** Q1 0.2256 0.2088 1.080 0.287 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 1.521 on 35 degrees of freedom (5 observations deleted due to missingness) Multiple R-squared: 0.03227, Adjusted R-squared: 0.004626 F-statistic: 1.167 on 1 and 35 DF, p-value: 0.2873 Here is my simple linear regression for gender based on the interest in the product: > reg2 = lm(Q13 ~ Q1, data = Josh_Batteer_Project_4) Results:
Residuals: Min 1Q Median 3Q Max -0.6690 -0.5871 0.3310 0.4129 0.5769 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.25916 0.25066 5.023 1.5e-05 *** Q1 0.08198 0.06895 1.189 0.242 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.5024 on 35 degrees of freedom (5 observations deleted due to missingness) Multiple R-squared: 0.03882, Adjusted R-squared: 0.01136 F-statistic: 1.413 on 1 and 35 DF, p-value: 0.2425 For my first question of whether or not household income and interest in the product is statistically significant, it seems that the two are not statistically significant. The p-value after running the simple linear regression was 0.287 which is not less than the 0.05 significance level. Therefore we cannot reject the null hypothesis and can conclude that somebody’s household income does not influence whether or not they would be interested in purchasing the product. For my second question of whether or not gender and interest in the product is statistically significant, it also seemed that the two were not statistically significant. The p-value after running the simple linear regression was 0.242 which is not less than the 0.05 significance level. Therefore we cannot reject the null hypothesis and can conclude that the respondent’s gender did not seem to have an impact on whether or not they would be interested in purchasing a solar powered charging phone case.
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