Course Contents
Introduction and Data Collection
Definition of statistics, Application in Business and Economics, Descriptive and Inferential Statistics, Types of Data (Categorical and Numerical), Classification of data (Cross-sectional, Time series, Pooled), Sources of Data (Primary and Secondary), Census and Sampling, Parameter and Statistics, Data Collection Technique, Questionnaire Construction.
Summarization of Data
Grouping and Displaying Data. Data array, Stem and Leaf Display, Frequency Distribution (Relative, Percentage and cumulative), Histogram (Frequency, Relative Frequency and Percentage), Frequency Polygon, Frequency Curve, Ogives, Bar Diagram, Pie Charts. Construction of Diagrams, Charts and Histogram using SPSS and their applications.
Numerical Descriptive Measures. Arithmetic Mean, Median, Mode, Midhinge, Midrange, Quartiles, Range, Standard Deviation, Variance, Coefficient of Variation, Shape (Symmetric and Skewed), Exploratory Data Analysis (Five Number Summary, Box and Whisker Plot), Application of Numerical Descriptive Measures and Analysis using SPSS.
Basic Probability: Concepts and Applications. Set Operations, Basic Concepts, Contingency Table, Simple and Joint Probability, Subjective and Objective Probability, Additive and Multiplicative Rules, Conditional Probability, Independence, Bays Theorem, Counting Rules, Application of Probability in Decision Making Process, Applications of Probability concepts and Analysis using SPSS.
Probability Distributions
Random Variable, Expectation ( Expected Value, Standard Deviation and Variance of a Discrete Random Variable), Application of Expectation in Decision Making Process, Binomial Distribution, Poisson Distribution, Normal Distribution.
Sampling Distribution and Estimation
Sampling, Types of Sampling, Sampling Distribution of Mean, Sampling Distribution of Proportion, Properties of Estimation, Point Estimation, Interval Estimation (Single Mean, Single Proportion, Difference between Two Means and Difference between Two Proportions), Sample Size Determination (Mean and Proportion), Connection between Confidence Level, Sample Size and Sampling Error.
Hypothesis Testing
Null and Alternative Hypothesis, Level of Significance, Confidence Level, Power of the Test, Type I and Type II Error, Critical Value, P-value, One and Two Tailed Test, Steps Involved in Hypothesis Testing, One Sample Test for Mean and Proportion, Two Samples Test for Mean (Independent and dependent) and Proportion.
Chi-Square Test and Analysis of Variance
Introduction, Cross Tabulation, Chi-Square as a Test of Independence, Comparison of Three or More than Three Means (One-Way Analysis of Variance). Application of Hypothesis Testing, Chi-Square Test and Analysis of Variance using SPSS.
Correlation and Regression Analysis
Correlation coefficient, Properties, Simple Linear Regression Model, Residual Analysis, Coefficient of Determination, Standard Error.
