# Business Statistics MAT 1430 Syllabus

Textbook: Business Statistics, 4th edition. Norean R. Sharpe, Richard D. De Veaux, and Paul F. Velleman, (c) 2019, Pearson Education Inc.

The content detail below covers material from Chapters 1-19.

Course Coordinator: Chelsea Romito

Catalog Course Description:
To introduce statistical concepts and methods useful in analyzing problems in all areas of business and economics.  In addition to learning the concepts, applications will be addressed in: Descriptive Statistics, Discrete and Continuous Probability Distributions, Sampling Distributions, Confidence Intervals, Hypothesis Testing, and Regression Analysis.

Objectives:
The purpose of this course is to provide the students with a sound conceptual and practical introduction to statistics and its applications in the business and economic fields.  Upon completion of the course, a student will be able:

• To recognize business situations that require the use of statistical tools of analysis.
• To select and execute the appropriate statistical tool for a specific business situation.
• To develop critical judgment and decision-making ability through the use of quantitative tools and statistical software.
• To address ethical issues when presenting and interpreting statistical information.

Topical Coverage:
I.   Numerical and Graphical Summaries
II.  Probability Distributions
III. Methods of Inferential Statistics
IV.  Regression and Correlation Analysis

 Content Descriptive Statistics Types of Variables (levels of measurement) Data Collection and Presentation Types of Sampling Methods Tables and Charts for Categorical Data (summary, bar, pie) Tables and Charts for Numerical Data Ordered Array Steam-and-Leaf Frequency Distributions (histogram) Cross Tabulations Contingency Tables Side-by-side bar charts Scatter Plots and Time Series Plots Numerical Descriptive Measures Measures of central tendency (mean, median, mode) Measures of dispersion (range, quartiles, interquartile range, variance, standard deviation) Shape of a distribution (skewness, box-and-whisker) Covariance between two variables Applications of mean with standard deviation Standardized (Z) scores Empirical Rule Probability and Probability Distributions Basic Probability Concepts - classical, relative frequency and subjective probabilities Discrete Probability Distributions Probability Distribution for a Discrete Random Variable Expected value of a probability distribution Standard deviation of a probability distribution Binomial Distribution Continuous Probability Distributions Normal Distribution Sampling Distributions Random Sampling Sampling Distributions of the Mean and Proportions Central Limit Theorem Confidence Interval Estimation Confidence Interval Estimation for one Mean (z and t distribution) Confidence Interval Estimation for one Proportion Sample size estimation Hypothesis Testing Hypothesis tests involving one mean or proportion Introduction to Type I Error, Type II Error, p-value Simple Linear Regression and Correlation Analysis Interpretation of slope and intercept The least-squares method Standard error of the estimate Coefficient of determination and correlation Estimation and testing of regression parameters Residual analysis Multiple Regression and Model Building Multiple regression model Significance tests in multiple regression Test of the overall significance of the model Test of the net regression coefficients Categorical explanatory variables (dummy variables) and interaction terms Multicollinearity Hypothesis Testing II Chi-Square Test Test for Difference of two proportions Test for differences among more than two proportions Test of Independence Test of Goodness-of-Fit Hypothesis tests involving two sample means, proportions or variances Analysis of Variance(optional)

### Contact Information

Department of Mathematics & Statistics
SAC Room 305
Villanova University
800 Lancaster Avenue
Villanova, PA 19085
Tel: 610.519.4850
Fax: 610.519.6928
Email: math@villanova.edu

Chair:
Dr. Jesse Frey

Staff: