Introduction to Statistics
- to give students the opportunity to get acquainted with the basic concepts of statistics
- to teach how to use statistical terms correctly and work with basic statistical concepts.
- know the difference between different measurement scales
- be able to explain the use of different methods in relation to a certain measurement scale
- know which charts are suitable for which type of data
- be able to formulate null and alternative statistical hypotheses
- be able to explain the rejection of statistical hypotheses
- be able to estimate the mean and variance of a sample
- The Where, Why, and How of Data CollectionData collection methods. Descriptive and inferential procedures. Sampling methods.
- Graphs, Charts, and Tables—Describing Your DataFrequency distribution. Histograms. Bar charts, pie charts, stem-and-leas diagrams. Line charts, scatter diagrams.
- Describing Data Using Numerical MeasuresMean, median, mode. Range, variance, standard deviation. Box and whisker graph. Z- scores.
- Introduction to ProbabilityApproaches to assessing probabilities. Addition rule and Multiplication rule. Conditional probability. Bayes’s Theorem.
- Discrete Probability DistributionsThe expected value. Binomial distribution. Poisson and hypergeometric distribution.
- Introduction to Continuous Probability DistributionsNormal distribution. Normal distribution table. Uniform and exponential distributions.
- Introduction to Sampling DistributionsSampling error. Standard deviation of sampling distribution. Central Limit Theorem.
- Estimating Single Population ParameterPoint estimate and confidence interval estimate. Z and t distributions. Sample size.
- Introduction to Hypothesis TestingNull and alternative hypothesis. Type I and Type II errors. Decision rule. Test statistic, critical values, p-value.
- Estimation and Hypothesis Testing for Two Population ParametersLogic of hypothesis testing. Independent population mean. Paired sample.
- Hypothesis Tests and Estimation for Population VariancesHypothesis tests for a single population variance. Chi-square distribution. Test variance difference.
- Analysis of VarianceANOVA. F – statistics.
- TestsThere will be three tests during the course. They are based on lecture as well as reading materials. Each test is assigned to chapters in the main course book.
- Final testThe final test includes 10 multiple choice questions about all topics studied during the course.