Course Content:
Unit 1 Describing Data using Graphs and Tables 4 hrs
Statistics in Business, Frequency distribution, Stem-and-leaf plots, Diagrams and Graphic presentation of Frequency distribution – Histogram, Ogive curve
Unit 2 Describing Data Using Numerical Measures 9 hrs
Measures of Central Tendency (Mean, Median and Mode), Partition values (quartiles, deciles and percentiles), Measures of variation (Range, Inter Quartile Range, quartile deviations), Variance and standard deviation, Coefficient of Variation, Skewness, Kurtosis, Five number summery, Box- Whisker plot,
Unit 3 Probability 5 hrs
Sample Space and Events, Probability, laws of probability, conditional probability, Baye’s
theorem.
Unit 4 Probability Distributions 5 hrs
Random variable, Mathematical Expectation , Binomial Distribution, Poisson Distribution, Normal Distribution.
Unit 5 Sampling Theory and Sampling Distributions 4 hrs Population and Sample, Sampling Methods, Central limit theorem, Sampling Distribution of Mean and Proportion.
Unit 6 Estimation 5 hrs
Estimation, Properties of Good Estimator: Consistency, unbiasedness, efficiency and sufficiency, Point and interval estimates, Margin of Error and Levels of Confidence, Confidence interval estimates for mean and proportion,
Unit 7 Introduction to Hypothesis Testing 7 hrs
Concept of Hypothesis Testing, Steps of Hypothesis Testing, Hypothesis Testing for Mean and Proportions for large Sample, Hypothesis Testing Using Critical Value approach, Confidence Limit approach, p-value approach.
Unit 8 Simple Linear Correlation 5 hrs
Scatter plot, Measures to describe correlation, Pearson's product moment correlation coefficient, Correlation Coefficient for Bi-Variate Data, test of significance of Sample Correlation Coefficient using Probable Error, Spearman's rank correlation coefficient
Unit 9 Simple Linear Regression 4 hrs
Linear models, Assumptions of the linear model, Linear regression model, Obtaining the least- squares linear regression model, interpretation of regression Coefficients,
