Lecture/discussion
Computerized application exercises. A significant component of this course requires individual usage of computer facilities.
- Review of Descriptive Statistics
. scales of measurement
. frequency distributions
. histograms, graphs and diagrams
. averages and variation
. using SPSS for computing frequencies, averages and variance
. cross-tabulation
- Introduction to SPSS
. setting up a data file
. defining data
. running SPSS/PC+
. the PRISM data base
- Probability and Probability Distributions
. approaches to probability
. measures of probability or expectation
. mutually exclusive events
. independent and dependent events
. conditional probabilities
. binomial, normal, and poisson distributions
- Sampling Theory and Techniques
. types of sampling
. surveys
. sampling distributions
- Statistical Inference
. population parameters and sample statistics
. sampling distribution of the mean
. standard error of the mean
. first limit theorem and central limit theorem
. estimation of the population mean
. confidence intervals
. sample size
. estimation of the population proportion
. z-scores, t-distribution, chi-square distribution
. using SPSS in statistical inference
- Hypothesis Testing
. null and alternative hypotheses
. test statistics
. test of significance, decision rule
. Type I and Type II error
. z-test, t-test, chi-square test
. using SPSS to test statistical hypotheses
- Examining Relationships
. correlation co-efficient (r)
. .linear regression
. standard error of the estimate
. co-efficient of determination
. using SPSS to calculate (r) and simple regression lines
At the end of the course, the successful student should be able to:
- Describe data using measures of central tendency and variability;
- Utilize SPSS statistical software to extract data from a database (PRISM), conduct basic statistical computations, and analyze the results.
- Calculate the probability of mutually exclusive, dependent or independent events; apply probability distributions to make estimates;
- Identify appropriate sampling techniques in order to make inferences about the population mean or proportion;
- Set up confidence intervals and conduct tests of significance for the population mean, proportion and variance using small or large samples;
- Set up and conduct tests of hypotheses and interpret results;
- Examine relationships between variables using correlation and linear regression.
Assignments (Minimum 4) 40%
Mid-term Exam 20%
Final Exam 30%
Participation 10%
100%
Textbooks and Materials to be Purchased by Students
Daniel W. Biostatistics: A Foundation for Analysis in the Health Sciences, 5th Edition, Wiley, 1991.
Raymond Yu. Research Applications I Manual for BUSN 337, Douglas College Printers, 1991.
Second semester standing or permission of instructor.
Research Applications II