BITM Business Statistics
bitmsemester 3
Unit 1:Describing Data using Graphs and Tables
Uses and scope of statistics in business and management. Frequency distribution. Stem-and-leaf plots. Diagrams (Simple bar diagram, Sub-divided bar diagram, Multiple bar diagram, and Pie-chart) and graphical presentation of frequency distribution – Histogram, Ogive curve. Problems using Excel.
Unit 2:Describing Data Using Numerical Measures
Measures of central tendency (Mean, Median and Mode). Partition values (Quartiles, Deciles and Percentiles). Measures of variation (Range, Inter quartile Range, Quartile deviations, Standard deviation). Variance and Coefficient of Variation. Measurement of skewness (Karl Pearson coefficient of skewness and Bowley coefficient of skewness). Measurement of kurtosis (Percentile coefficient of kurtosis). Five number summery. Box-and-Whisker plot. Problems using Excel.
Unit 3:Simple Linear Correlation Analysis
Introduction. Scatter plot. Karl Pearson's correlation coefficient including bi-variate frequency distribution. Coefficient of determination. Test of significance of sample correlation coefficient using probable error. Spearman's rank correlation coefficient. Problems using Excel.
Unit 4:Simple Linear Regression Analysis
Introduction. Simple linear regression models. Assumptions of linear regression model. Line of best fit. Linear regression model by least-squares method. Interpretation of regression coefficients. Properties of regression coefficient. regression coefficient for bi-variate frequency distribution. Problems using Excel.
Unit 5:Probability
Introduction. Sample space and events. Probability. Laws of probability. Conditional probability. Problems using Excel.
Unit 6:Probability Distributions
Introduction. Discrete probability distribution (Binomial distribution and Poisson distribution). Continuous probability distribution (Normal distribution). Problems using Excel.
Unit 7:Sampling Theory
Introduction. Population and sample. Objectives of sampling. Sampling techniques. Sampling and non-sampling errors. Standard error. Concept of central limit theorem.
Unit 8:Estimation
Introduction. Properties of good estimator (Consistency, Unbiasedness, Efficiency and Sufficiency). Point and interval estimates. Level of confidence. Confidence interval estimates for mean and proportion. Determination of sample size for mean and proportion. Problems using Excel.
Unit 9:Introduction to Hypothesis Testing
Introduction. Steps of hypothesis testing. Level of significance. Critical region. One tailed test and two tailed test. Hypothesis testing using critical value and p-value approaches. Test of significance for large samples (Z-test): Test of significance of a single mean and difference between two means, Test of significance of a single proportion and difference between two proportions. Problems using Excel.