James M. Sinacore, Ph.D.
Dept. of Preventive Medicine and Epidemiology
Loyola University Stritch School of Medicine
General Course Objectives
classify statistical analysis as a collection of techniques that are intended to uncover
information in data.
discuss how statistical methods are used as a research tools.
describe the purpose and proper use of the statistical techniques presented in class.
define basic statistical concepts.
conduct statistical tests of research hypotheses using methods presented in class.
Desired course outcomes
Understand biomedical applications of topics discussed i.e. descriptive statistics, hypothesis testing, t-tests, chi-squared test, analysis of variance, etc.
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Artifacts:
Student's t-test et el.pdf
Chi Squared_visual.pdf
Chi-Square_levels 0f sig.pdf
ANOVA F ratio.doc
Statistics_ P-values and Alpa...pdf
The Student's t-test et el.pdf contains a short synopsis of the courses basic formulas; Means, Confidence levels, standard scores, Chi Squared and Student’s t-test for related samples. While the t-test is used to compare the means between two groups, ANOVA is used to compare means between 3 or more groups. The ANOVA F ratio.doc” summaries the varieties of ANOVA, such as one-factor (or one-way) ANOVA, two-factor (or two-way) ANOVA, and so on, and also repeated measures ANOVA. The factors are the independent variables, each of which must be measured on a categorical scale - that is, levels of the independent variable must define separate groups. The chi-square test (Snedecor and Cochran, 1989) is used to test if a sample of data came from a population with a specific distribution. It is useful because, under reasonable assumptions, easily calculated quantities can be proven to have distributions that approximate to the chi-square distribution if the null hypothesis is true. The Chi Squared_visual.pdf” relates Chi Squared to the normal distribution, and Chi-Square_levels of sig.pdf is a chart for degrees of freedom and level of significance. The Statistics_ P-values and Alpa...pdf is an interesting article on is a measure of how confident we can be that what we observe in the sample is also true for the population. The P-value is important in inference. We infer from what we see in the sample to the population. This course was critical to my understanding of statistical significance and the analysis of data.
Main Take-A-Way
Statistical analysis is a collection of techniques used to uncover information in data. Data can be presented in many ways and without analytical tools to assess the reality in the information the data would have questionable value..
Areas of Strength
Strong understanding of the biomedical applications of the statistical analysis techniques reviewed above.
Areas for Development
I could use practical experience working with statistical design for real world studies or experiments.