Course Contents
WHAT IS STATISTICS
Definition of Statistics, Population & sample, Descriptive and Inferential Statistics, Observations, Discrete and continuous variables, collection of primary and secondary data and sources, Introduction of SPSS.
PRESENTATION OF DATA
Introduction, Basic principles of classification and tabulation, Construction of a frequency distribution, Relative and Cumulative frequency distribution, Diagrams and Graphs and their construction, Bar Charts, Pie Charts, Histogram, Frequency Polygon and Frequency Curve, Historigram, Types of frequency Curves. Exercise on SPSS.
MEASURES OF CENTRAL TENDENCY
Introduction, Different types of Averages, Mean, Median and Mode, Quantiles, Empirical relation between Mean, Median and Mode, Merit and Demerits of various Averages, Box and Whisker Plot, Definition of outliers and their detection. Exercise on SPSS.
MEASURES OF DISPERSION
Introduction, Absolute and relative measures, Range, The Semi Inter-Quartile Range, Variance and Standard Deviation, Interpretation of Standard Deviation, Co-efficient of Variation, Standardized Variables. Exercise on SPSS.
PROBABILITY AND PROBABILITY DISTRIBUTION
Concept of discrete and continuous distribution, Normal distribution. Exercise on SPSS.
SAMPLING AND SAMPLING DISTRIBUTION
Introduction, sample design and sample frame, bias, sampling and non sampling errors, sampling with and without replacement, probability and non-probability sampling, Simple Random sampling, Stratified Random Sampling, Systematic and cluster sampling, Sampling Distribution for single mean and proportion. Exercise on SPSS.
HYPOTHESIS TESTING
Introduction, Statistical problem, null and alternative hypothesis, Type-I and Type-II Errors, Level of significance, Test Statistics, Acceptance and rejection regions, general procedure for testing of Hypothesis.
TESTING OF HYPOTHESIS –INDEPENDENCE OF ATTRIBUTES
Introduction, Contingency Tables, Testing of Hypothesis about the independence of attributes. Exercise on SPSS.
REGRESSION AND CORRELATION
Introduction, cause and effect relationships and examples, simple linear regression, estimation of parameters and their interpretation, r and R^2. Correlation, coefficient of linear correlation, its estimation and interpretation, Multiple regression and interpretation of its parameters. Exercise on SPSS.
Course Learning Outcomes
The course is designed to impart the knowledge of Statistics and utilizing SPSS software to present and analyze the data of different fields.
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Book Title : Introduction to Statistical theory, Part-I
Author : Ch. Sher Muhammad and dr. shahid kamal
Edition : 8th
Publisher : Ilmi Kitab Khana, Lahore. Pakistan.
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Title : Multiple Regression Analysis - Stanford University
Type : Presentation
View Multiple Regression Analysis - Stanford University