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Amity Syllabus of Statistics for Management
Module I Introduction
- Statistical thinking and analysis ;
- Statistics defined; Types of statistical methods – Descriptive and inferential statistics; Importance and scope of statistics ;.
- Scales of measurement;
- Basic statistical concepts: population and sample.
Tabular and Graphical Descriptive Techniques using MS Excel: - Bar chart, Pie Chart, Histogram, Frequency Polygon, Ogive, Pareto Chart.
- Stem-and-leaf display, Cross tabulations, Scatter plot and Trend line.
Numerical Measures - Arithmetic Mean, Median and Mode.
- Partition Values- Quartiles, and percentiles.
- Measures of Variability: Range, IQR; Variance, Standard Deviation, Coefficient of variation.
- Use of MS Excel for Numerical Measures
Module II Probability and Probability Distributions
- Types of events and Algebra of events. Assigning probability to events;
- Joint, Marginal and Conditional Probability.
- Probability Rules; complement Rule, Multiplication Rule, Addition Rule, Bayes¡¦
Theorem.
Probability Distributions: - Mean or Expected value of random variable.
- Variance and Standard Deviation of random variables.
- Binomial Probability Distribution, Poisson Probability Distribution and Normal
Probability Distribution. - Using MS Excel for computation of Binomial, Poisson and Normal probabilities.
Module III Sampling, Sampling Distribution and Estimation
- Sampling: Basic Concepts, Types of Sampling and Non-Sampling Errors and
Precautions, - Central Limit Theorem,
- Sampling Distribution of the mean, Sampling distribution of proportion.
- Estimation: Types Estimates, Using z Statistic for estimating population mean,
- Confidence interval for estimating population mean when population SD is unknown,
- Estimating population mean using t Statistic (small sample case), and Confidence interval estimation for population proportion.
- Using MS Excel for confidence interval construction.
Module IV Hypothesis Testing
Fundamental Concepts of Hypothesis Testing:
- Developing null and alternate hypothesis,
- Hypothesis testing procedure, the critical value of the test statistic, regions and rejection and non-rejection,
- Type I error and Type II error,
- Level of significance,
- The confidence coefficient, The power of a test,
- The p-value approach to hypothesis testing.
Inference about a Population: - For single population mean using z-statistic, for single population mean using t-statistic, hypothesis testing for population proportion.
Inference about Comparing Two Populations: - Inference about the difference between two population means ‘
- Independent samples and Matched Samples,
- Inference about the difference between two population proportions, Inference about the ratio of two population variances.
Analysis of Variance (Analysis and Interpretation of MS Excel Output only): - Testing for equality of k- population means,
Chi-Squared Tests: - Chi-squared goodness of fit test for mean, and test of independence. Using MS Excel for
Chi-squared test.
Module V Forecasting Techniques
- Measures of Linear Relationship: covariance, coefficient of correlation.
- Regression: Model, Estimating the coefficient using least squares method. Assessing the
Model (Analysis and Interpretation of Excel Output only); - Standard Error of Estimate, Coefficient of determination,
Time Series Analysis: - Variation in Time Series, Numerical application of trend analysis only.
