Statistics I

DESCRIPTION:
Organizing and summarizing data. Probability distributions: binomial, Poisson, normal, t-distribution, chi-square. Sampling and sampling distribution of the mean. The central limit theorem. The course is not open to students who have completed an MA-course in statistics.

RATIONALE: 
The course focuses on descriptive statistics and probability distributions. The students learn to summarize and describe data, and calculate probabilities using the binomial, Poisson and normal distributions.

LEARNING OUTCOMES: 
1. Summarize a set of data by constructing a frequency distribution table and obtain a graphical representation with the use of bar charts, pie charts and histograms.
2. Find and interpret measures of location (mean, median, mode, percentile) and measures of variation (range, standard deviation, variance) for a sample or population.
3. Apply discrete probability distributions to determine probabilities of random events.
4. Apply the normal distribution, the central limit theorem, the family of tdistributions and the family of χ2 -distributions.
5. Utilize EXCEL for data presentation and probability calculation and interpret relevant outputs.

METHOD OF TEACHING AND LEARNING:
In congruence with the teaching and learning strategy of the college, the following tools are used:
- Class lectures, interactive learning (class discussion, group work), video presentations, and practical problems solved in class.
- Lab periods will be used to cover probability theory and enhance concepts
- Exercises and primary source documents are assigned as homework, the solutions of which are reviewed in class.
- Office hours: Students are encouraged to make full use of the office hours of their instructor, where they can ask questions, see their exam paper, and/or go over lecture material.
- Use of the blackboard site, where instructors post lecture notes, assignment instructions, timely announcements, as well as additional resources.