Descriptive Statistics
Descriptive Statistics
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Module 3 – SLP
One-Sample and Two-Sample Tests
Using the provided dataset in Excel, calculate the appropriate descriptive statistics for the following variables comparing diabetes with no diabetes status: gender, race, salary, education, height, weight, BMI, allergies, family history diabetes, family history allergies. For chi-square tests, report the chi-square value and the p-value (if p-value < 0.05, then the test is significant). For t-tests, report the t-test value and the p-value. Include a 2-3 page description of the descriptive statistics including tables of the summarized data, similar to a “Results” section in a published manuscript or journal article. Use the following online calculators to obtain the results for this analysis.
Chi-Square for Categorical Data: http://www.vassarstats.net/ (Choose “Frequency Data” from the far left, then “Chi-Square, Cramer’s V, and Lambda” from the middle of the page)
Enter in the number of people in each category (e.g. number of women who have diabetes, number of men with diabetes, etc.). Example of a table below:
Diabetes No Diabetes
Female 86 214
Male 36 264
Choose a 2 x 2 table and where A1 = 86, A2 = 36; B1 = 214; B2 = 264
Report the percent of people in each category and the chi-square and p-value. A possible sentence to interpret the results could be:
There are significantly more women (64%) who have diabetes than men (36%).
T-Tests for Continuous Data: http://www.vassarstats.net/ (Choose “t-Tests & Procedure” from the far left, then “Two-Sample t-Test” then click “Independent Samples” under Setup)
Copy and Paste the values for those with diabetes into Sample A and those without diabetes into Sample B, then click Calculate. For instance, copy and paste all of the ages of those with diabetes into Sample A and all of the ages of those without diabetes into Sample B. From the Data Summary window, report the Mean of those with Diabetes (Sample A) and those without Diabetes (Sample B); also report the “t” from the Results box, as well as the two-tailed p-value. A “P” that is <0.05 suggests the result is statistically significant. One way to report such a finding would be to use the following language:
The average age of those with diabetes is __ years and for those without diabetes is ___ years. Those with diabetes were significantly older/younger (p<0.05).
SLP Assignment Expectations
Length: SLP assignments should be at least 2 pages (500 words) in length.
References: At least two references must be included from academic sources (e.g. peer-reviewed journal articles). Required readings are included. Quoted material should not exceed 10% of the total paper (since the focus of these assignments is critical thinking). Use your own words and build on the ideas of others. When material is copied verbatim from external sources, it MUST be enclosed in quotes. The references should be cited within the text and also listed at the end of the assignment in the References section (APA format recommended).
Organization: Subheadings should be used to organize your paper according to question
Format: APA format is recommended for this assignment. See Syllabus page for more information on APA format.
Grammar and Spelling: While no points are deducted for minor errors, assignments are expected to adhere to standards guidelines of grammar, spelling, punctuation, and sentence syntax. Points may be deducted if grammar and spelling impact clarity.
The following items will be assessed in particular:
•Achievement of learning outcomes for SLP assignment.
•Relevance—all content is connected to the question.
•Precision—specific question is addressed; statements, facts, and statistics are specific and accurate.
•Depth of discussion—points that lead to deeper issues are presented and integrated.
•Breadth—multiple perspectives and references, multiple issues/factors considered/
•Evidence—points are well-supported with facts, statistics, and references.
•Logic—presented discussion makes sense; conclusions are logically supported by premises, statements, or factual information.
•Clarity—writing is concise, understandable, and contains sufficient detail or examples.
•Objectivity—use of first person and subjective bias are avoided.
I can send the provided assignment excel dataset download if you provide where to send to. Thanks
SAMPLE ANSWER
Descriptive Statistics
Using the provided dataset in Excel, descriptive statistics that are appropriate for variables concerning to diabetes including gender, race, salary, height, weight, as well as BMI. The descriptive statistics calculated using the provided dataset specifically include mean, standard deviation, variance as well as media. These descriptive statistics are mainly concerned with analysis of measurement of central tendency i.e. mean and median as well as measurement of variation i.e. standard deviation and variance.
Table 1: Descriptive Statistics
| Age | Salary | Height | Weight | BMI | To feel depressed during the winter | To exercise during the summer | To overeat when stressed out | |
| Mean | 50 | $54,498 | 66.98333 | 159.1133 | 24.63867 | 2.993333 | 3.373333 | 2.77 |
| Standard Deviation | 20 | 28923.783 | 3.750102 | 31.66517 | 2.231375 | 1.226773 | 1.227046 | 1.315116638 |
| Variance | 401 | 836585199 | 14.06327 | 1002.683 | 4.979035 | 1.504972 | 1.505641 | 1.729531773 |
| Median | 50 | $50,012 | 67 | 161 | 25 | 3 | 4 | 3 |
In particular, this SLP assignment will be analyzed the provided dataset using chi-square tests and t-test. For the chi-square tests apart from the descriptive statistics, the report will also include chi-square value as well as the p-value. On the other hand, for the t-tests the report will include the t-test value as well as the p-value.
In addition, the specific numbers of people in the provided the dataset within their specific category i.e. diabetes and no diabetes are determined in order to enable the data analysis to be carried out. A summary of those statistics is presented in the table shown below:
Table 2: Data Summary
| Diabetes | No Diabetes | Total | Percentages | |
| Female | 56 | 103 | 159 | 53% |
| Male | 53 | 88 | 141 | 47% |
| Total | 109 | 191 | 300 | |
| Percentages | 36.3% | 63.7% | 100% |
Based on the statistics presented in the above table concerning the chi-square obtained from the VassarStats website which is used for statistical computation, particularly in the context of Chi-Square for Categorical Data and specifically using Chi-Square, Cramer’s V, and Lambda in a 2 x 2 table; there are some inferences that can already be done. Some of the inferences based on percentages include:
There are significantly more women (53%) who have diabetes than men (47%).
Additionally, the results of the chi-square test show that the chi-square value is 0.09 and the p-value is <0.0001 an indication that the test is significant meaning that there a significant difference between the number of women who are diabetic compared to men who are diabetic.
T-Tests for Continuous Data
The t-test was used to compare the two groups i.e. Sample A (no diabetes) and Sample B (diabetes) and the t-test reported the t-test value as well as p-value. The t-test values for variables such as age, height, weight as well as BMI are reported in the table shown below. In addition, the two-tailed p-values are also shown and the are all below <0.05 and indication that the tests are significant which means there are significant differences between the two groups (i.e. Sample A and Sample B) with regards to the considered variables.
Table 3: Data Summary
| A | B | Total | t-test value | Two-tailed p-value | ||
| N | 191 | 109 | 300 | |||
| Age | Mean | 39.0052 | 70.5229 | 50.4567 | -20.69 | <0.0001 |
| Height | Mean | 65.0209 | 70.422 | 66.9833 | -16.63 | <0.0001 |
| Weight | Mean | 142.7016 | 187.8716 | 159.1133 | -16.33 | <0.0001 |
| BMI | Mean | 23.5628 | 26.5239 | 24.6387 | -14.35 | <0.0001 |
The average age of those without diabetes is 39 years and for those with diabetes is 70.5 years. Those with diabetes were significantly older/younger (p<0.05).
The average height of those without diabetes is 65.02 centimeters and for those with diabetes is 70.4 centimeters. Those with diabetes were significantly shorter/taller (p<0.05).
The average weight of those without diabetes is 132.7 lbs and for those with diabetes is 187.8 lbs. Those with diabetes were significantly heavier/lighter (p<0.05).
The BMI of those without diabetes is 23.6 and for those with diabetes BMI is 26.5. The BMI for those with diabetes is significantly higher/lower (p<0.05).
References
Corder, G. W. & Foreman, D. I. (2014). Nonparametric Statistics: A Step-by-Step Approach. New York, NY: Wiley.
Greenwood, P. E. & Nikulin, M. S. (1996) A guide to chi-squared testing. New York, NY: Wiley.
Markowski, C. A. & Markowski, E. P. (1990). Conditions for the Effectiveness of a Preliminary Test of Variance. The American Statistician, 44(4), 322–326.
Sawilowsky, S. S. (2005). Misconceptions Leading to Choosing the t Test over the Wilcoxon Mann–Whitney Test for Shift in Location Parameter. Journal of Modern Applied Statistical Methods, 4(2), 598–600.
VassarStats (2015). Procedures Applicable to Categorical Frequency Data. Available at: http://www.vassarstats.net/ (Accessed on November 26 2015).
VassarStats (2015). t-Tests & Procedures. Available at: http://www.vassarstats.net/ (Accessed on November 26 2015).
Zimmerman, D. W. (1997). A Note on Interpretation of the Paired-Samples t Test. Journal of Educational and Behavioral Statistics, 22(3), 349–360.
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