Statistical Analysis Report 40% of your final grade Using the anthropometric

Statistical Analysis Report 40% of your final grade Using the anthropometric and power data collected from Physical Therapy students, carry out

an analysis of the data to answer the following question. ” Is there a relationship between anthropometric data and leg power in male and female physiotherapy students?” I suggest that you analyse the data within the following framework.

1. Descriptive analysis of anthropometric and power data

2. Analysis of differences among/between variables as appropriate 3. Analysis of association among/between variables as appropriate For each set of analysis:

1. define the nature/level of data

2. the statistical test used

3. the function of the test 4. state clearly the outcome of the analysis 5. interpret the

results of the analysis If you use tables or graphical representation to illustrate your analysis, explain in words what the table/graph illustrates.

Be selective about your choice of statistical tests! Don’t use every test on the menu! In addition to the actual analysis, points will be awarded for

 

presentation and interpretation of the data. The report needs to be double spaced with a font size of 12 Length: 1200 words (not including tables

and graphs)

 

SOLUTIONS 

 

  1. Descriptive analysis of anthropometric and power data:

  2. Nature/level of data: The anthropometric and power data are continuous numerical variables.

  3. Statistical test used: Descriptive statistics such as mean, median, standard deviation, range, and frequency distributions are used to summarize and describe the data.

  4. Function of the test: The descriptive analysis provides a summary of the data, which helps in understanding the central tendency, variability, and distribution of the data.

  5. Outcome of the analysis: The outcome of the analysis includes descriptive statistics such as mean, median, standard deviation, range, and frequency distributions.

  6. Interpretation of the results: The interpretation of the results involves understanding the central tendency of the data (mean or median), the spread of the data (standard deviation or range), and the distribution of the data (skewed or normal).

  7. Analysis of differences among/between variables as appropriate:

  8. Nature/level of data: The variables being compared can be continuous or categorical.

  9. Statistical test used: Depending on the nature and level of the data, different statistical tests can be used such as t-test, ANOVA, chi-square test, or Mann-Whitney U test.

  10. Function of the test: The analysis of differences is used to compare the means or proportions of two or more groups to determine if there are significant differences between them.

  11. Outcome of the analysis: The outcome of the analysis is a statistical value such as t-statistic, F-statistic, or chi-square value, along with a p-value.

  12. Interpretation of the results: The interpretation of the results involves understanding if the p-value is less than the alpha level (usually 0.05), which indicates that there is a statistically significant difference between the groups being compared.

  13. Analysis of association among/between variables as appropriate:

  14. Nature/level of data: The variables being analyzed can be continuous or categorical.

  15. Statistical test used: Depending on the nature and level of the data, different statistical tests can be used such as correlation analysis, regression analysis, or chi-square test.

  16. Function of the test: The analysis of association is used to determine if there is a relationship or correlation between two or more variables.

  17. Outcome of the analysis: The outcome of the analysis is a statistical value such as correlation coefficient or regression coefficient, along with a p-value.

  18. Interpretation of the results: The interpretation of the results involves understanding the strength and direction of the association between the variables, as indicated by the correlation coefficient or regression coefficient. A p-value less than 0.05 indicates that the association is statistically significant.