Business Statistics |
Contents
Introduction | 1 |
Statistics as a Scientific Method | 7 |
Functions Importance Limitations and Distrust of Statistics | 11 |
Statistical Investigation | 19 |
Census and Sample Investigation | 23 |
Collection Editing and Analytical Tools of Data | 37 |
Classification and Tabulation of Data | 49 |
Diagrammatic Presentation | 71 |
Probability | 461 |
Merits and Limitations of Coefficient | 471 |
Probability Distribution of a Random Variable and Decision Analysis | 521 |
Value Index | 545 |
Theoretical Probability Distributions | 555 |
Calculation of Inflation | 567 |
Stock Market Index | 576 |
Sampling Distributions | 601 |
Graphic Presentation | 89 |
Measures of Central Tendency | 109 |
Measures of Dispersion | 193 |
Classification and Tabulation | 226 |
Moments Skewness and Kurtosis | 241 |
Diagrammatic Presentation | 260 |
Correlation | 265 |
72 | 268 |
Correlation in a Bivariate | 277 |
Regression Analysis | 297 |
Index Numbers | 329 |
Analysis of Time Series | 387 |
Theory of Attributes | 435 |
Seasonal Variations | 612 |
Statistical Inference | 619 |
Consistency of Data | 631 |
Analysis of Variance | 683 |
Multiple Linear Regression | 695 |
Statistical Quality Control | 709 |
Nonparametric Tests of Hypothesis | 727 |
Wilcoxon MatchedPairs Signed | 733 |
Appendix | 741 |
Generalisation to the Case of m Variables | 748 |
Answers | 753 |
Common terms and phrases
analysis antilog arithmetic mean balls Bar Diagram base binomial distribution Calculate characteristics class intervals classification coefficient of correlation collected commodity Compute cumulative frequency curve defective denote determine equal estimate event Example figures Find the probability following data following table gives formula frequency distribution geometric mean given graph Hence Hint hypothesis income independent index numbers interquartile range large number less level of significance limits M₁ marks obtained mean and standard mean deviation measure of dispersion median method mid-value mode monthly n₁ n₂ normal distribution number of observations P₁ percentage persons Poisson Poisson distribution population probability distribution production quartile random sample random variable ratio regression coefficients respectively Similarly simple random sample skewness Solution standard deviation standard error statistics sum of squares termed trend values units variance variations various wages weights workers write X₁ Y₁ ΣΧ