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Analyzing Survey Data Using Statistical Tests

Posted on | by Kelvin

In this conversation, we’ll explore the data from our weekly surveys. Your instructor will provide you with the Excel worksheet which contains the data from the surveys completed in this course. The worksheet will also contain data for Dayton in particular.
What will you do with the data? Throughout the course, you have examined many different statistical analyses and their purpose and function. Be sure to visit your lifeline to determine the correct test and to refresh your memory on how to run statistical analyses in Excel.

DISCUSSION INSTRUCTIONS
Describe the statistical test you chose to run on the data. Why is the test appropriate from the data you chose to manipulate?
State the hypotheses for the test you are running on the data (alternative/research hypothesis and null hypothesis).
Provide the output table for your results. Were they significant? What does your test tell us about the data and why might it be useful?
In your responses to peers, take on the role of a journalist interviewing the original postee and asking them pertinent questions about their use and choice of data. Original respondents will then answer the journalists’ questions and justify their manipulation of the data.

 

 

Sample Answer

Analyzing Survey Data Using Statistical Tests

Introduction

In this analysis, we will explore the statistical test chosen to analyze the survey data provided in the Excel worksheet. The purpose of this analysis is to draw insights from the data and make informed decisions based on the statistical results obtained.

Statistical Test: One-Way Analysis of Variance (ANOVA)

Reason for Choosing the Test: ANOVA is suitable for comparing means between three or more groups, which is often the case in survey data where responses may vary across different categories or variables.

Hypotheses:

– Null Hypothesis (H0): There is no significant difference in survey responses among the different groups.
– Alternative Hypothesis (H1): There is a significant difference in survey responses among the different groups.

Output Table for Results

Source of Variation Sum of Squares Degrees of Freedom Mean Square F-Value p-value Significance
Between Groups xxx xx xx xx xx Yes/No
Within Groups xxx xx xx
Total xxx xx

– Significance: If the p-value is less than 0.05, we reject the null hypothesis and conclude that there is a significant difference in survey responses among the groups.

Interpretation of Results

– Significance: If the p-value is less than 0.05, we reject the null hypothesis and conclude that there is a significant difference in survey responses among the groups.
– Usefulness: The test provides valuable insights into how survey responses vary among different categories or variables, helping us identify areas of strength or improvement based on the data collected.

By conducting the ANOVA test on the survey data, we can gain a better understanding of how responses differ across various groups and make informed decisions to enhance our strategies or initiatives based on the statistical findings.

 

 

 

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