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Dersin Haftalık Planı

Hafta Konu
1 Pretest, Introduction to Probability and Statistic, Course Objectives
2 The Definition of Statistics.
Classification of Statistics; Descriptive and Inferential Statistics
Data Description and Graphical Methods:
3 Histogram, Stem and Leaf Diagrams, Frequency distributions, box plots.
4 Numerical Methods of Describing Data: (for Ungrouped and Grouped data)
Measure of Central Tendency, Measure of Variability, Measure of Relative Standing.
5 Normal distribution, Moments-Parameters of Distribution; Skewness, Kurtosis,
Some computer applications.
6 Approaches to the theory of probability, definition of probability.
Fundamentals of Probability, basic concepts: experiment, outcome, sample space, event, elementary event, event space.
7 Computing Probabilities: Set algebra, Combinatorial analysis: Basic principle of counting,
Permutations, Combinations.
8 Conditional Probability and Independence. Bayes formula.
Conditional probability applications and examples,
9 Bernoulli trials, Binomial distribution
Random Variables, Probability Distributions Functions
10 Random Variables, Probability Distributions Functions
11 Probability Distributions Functions, Probability Density Function, Expectations and Moments
12 Sampling Distribution, Sampling Theory, Random Sampling, Central Limit Theorem,
Statistical Inference: Small Sample Results
13 Statistical Inference: Small Sample Results
Statistical Inference: Large Sample
14 General Linear Models and Applications
Correlation Theory, Computer Applications, The Chi-Square Test; Time Series
 
 
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