Artificial Intelligence
Please fill the required field.

Generate and analyze this hypothesis and the data using independent sample t-test : Hypothesis H0: There is no significant difference between the effect of green packaging of male and female individuals in Wa municipality. H1: There is a significant


To analyze the given hypothesis using the independent samples t-test, let's break down the information and the steps involved: ### Hypothesis 1. **Null Hypothesis (H0)**: There is no significant difference between the effect of green packaging on male and female individuals in the Wa municipality. 2. **Alternative Hypothesis (H1)**: There is a significant difference between the effect of green packaging on male and female individuals in the Wa municipality. ### Given Data - For Males: - N (sample size) = 80 - Mean = 20.68 - SD (Standard Deviation) = 3.14 - For Females: - N (sample size) = 120 - Mean = 20.05 - SD = 3.56 ### Additional Information - Degrees of freedom (df) = 198 - t-value = 1.307 - Significance (2-tailed) = 0.193 ### Steps for Analysis 1. **Assumptions of the Independent Samples T-Test**: - Normality: The data within each group should be normally distributed. - Homogeneity of variance: The variances of the two groups should be equal. 2. **Calculate the Test Statistic**: The t-statistic has already been provided. The value of t is calculated based on the means, standard deviations, and sample sizes of both groups. 3. **Determine the Critical Value**: The critical value depends on the significance level (commonly, α=0.05 for a 95% confidence level) and the degrees of freedom (df = 198). Using a t-distribution table or calculator, we can find the critical t-value for df = 198 at α=0.05 for a two-tailed test, which is approximately ±1.972. 4. **Decision Rule**: - If the absolute value of the calculated t-value is greater than the critical t-value, we reject the null hypothesis. - If the absolute value of the t-value is less than the critical t-value, we do not reject the null hypothesis. 5. **Analysis of Results**: - Given t-value = 1.307 - Critical t-value (two-tailed, df = 198, α = 0.05) = ±1.972 Since 1.307 < 1.972, we do not reject the null hypothesis. ### Conclusion There is not enough evidence to conclude that there is a significant difference between the effects of green packaging on male and female individuals in Wa municipality as the significance value (0.193) is greater than the typical alpha level (0.05). Therefore, we accept the null hypothesis (H0) and conclude that the effect of green packaging does not significantly differ between genders in this sample. ### Summary - **t-statistic**: 1.307 - **p-value (Sig (2-tailed))**: 0.193 - **Decision**: Fail to reject H0. - **Conclusion**: No significant difference between the impact of green packaging on males and females in Wa municipality.