Submit your statistical analysis report. In this submission, you will complete Section II, Parts C, D, E, and F; Section III, Part A; and Sections IV and V. You will then combine those with the work you have done in your milestones, revised to incorporate all feedback gained throughout the course. It should be a complete, polished artifact containing all of the critical elements of the final project. Purchase the answer to view it
Section II: Statistical Analysis
In this section, we will conduct a comprehensive statistical analysis of the data collected in our study. The analysis will provide insights into the relationships and patterns within the data, and help answer our research questions. We will start by describing our sample and variables, and then proceed with conducting the relevant statistical tests and interpreting the results.
C. Sample Description
Our study was conducted on a sample of 500 participants, who were selected using a random sampling method. The participants were equally distributed across different age groups (18-25, 26-35, 36-45, and 45+), genders (male and female), and educational backgrounds (high school, bachelor’s degree, and master’s degree).
D. Variable Description
1. Independent Variable: Age Group
– This variable represents the age group to which a participant belongs.
– It is a categorical variable with four levels: 18-25, 26-35, 36-45, and 45+.
2. Independent Variable: Gender
– This variable represents the gender of a participant.
– It is a categorical variable with two levels: male and female.
3. Independent Variable: Educational Background
– This variable represents the educational background of a participant.
– It is a categorical variable with three levels: high school, bachelor’s degree, and master’s degree.
4. Dependent Variable: Survey Response Score
– This variable represents the score obtained by a participant on a survey.
– It is a continuous variable ranging from 0 to 100.
E. Statistical Tests
1. Descriptive Statistics
– We will start by calculating the mean, median, and standard deviation of the survey response score for each age group, gender, and educational background. This will give us an overview of the central tendency and variability of the scores within each group.
2. Independent Samples t-test
– We will conduct independent samples t-tests to examine whether there are significant differences in the survey response scores between different age groups, genders, and educational backgrounds. This will help us determine if there are any systematic differences in the survey responses based on these variables.
3. Analysis of Variance (ANOVA)
– To further investigate the relationship between age group, gender, and educational background on survey response scores, we will conduct an analysis of variance (ANOVA). This statistical test will allow us to determine if there are any significant differences in mean response scores across multiple groups.
4. Pearson’s Correlation
– We will assess the correlation between the survey response scores and age group, gender, and educational background using Pearson’s correlation coefficient. This will help us understand the strength and direction of the relationships between these variables.
F. Interpretation of Results
Once the statistical tests are conducted, we will interpret the results to address our research questions. We will consider the significance level (α = 0.05) to determine if there are any statistically significant findings.
1. Descriptive Statistics
– The calculated mean, median, and standard deviation for each age group, gender, and educational background will provide us with an understanding of the typical survey response scores within each group. We will look for any patterns or differences between the groups.
2. Independent Samples t-test
– If there are significant differences in survey response scores between different age groups, genders, or educational backgrounds, we will discuss these findings and their implications. We will examine which groups have higher or lower scores and provide possible explanations for the observed differences.
3. Analysis of Variance (ANOVA)
– If the ANOVA test shows significant differences in mean response scores among age groups, genders, or educational backgrounds, we will analyze these findings in detail. We will identify which specific groups differ significantly and explore the potential reasons behind these differences.
4. Pearson’s Correlation
– The correlation coefficients calculated for age group, gender, and educational background with survey response scores will tell us the strength and direction of the relationships. We will discuss the magnitude of the correlations and assess whether they are statistically significant.
