BITM Business Statistics

bitmsemester 3

This course introduces the students to statistical tools and techniques which are applied to in business decision-making. The course will cover the basic tools used to describe data for the purposes of transforming data into information. In addition, the course will present the fundamentals of statistical inference showing how it is possible to examine a small subset of data to reach conclusions about the larger set of data. The statistical tools should be introduced from an applied perspective using business related examples. Microsoft Excel software will be used throughout the course to aid in statistical analysis.

semester photo

Chapter Wise Notes Question Banks Syllabus Chapter Wise Questions Viva Practical

Unit 1:Describing Data using Graphs and Tables

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

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

Sample Space and Events, Probability, laws of probability, conditional probability, Baye's theorem.

Unit 4:Probability Distributions

Random variable, Mathematical Expectation, Binomial Distribution, Poisson Distribution, Normal Distribution.

Unit 5:Sampling Theory and Sampling Distributions

Population and Sample, Sampling Methods, Central limit theorem, Sampling Distribution of Mean and Proportion.

Unit 6:Estimation

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

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

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

Linear models, Assumptions of the linear model, Linear regression model, Obtaining the least-squares linear regression model, interpretation of regression Coefficients.