LSC Business Statistics (Online Course WebCT)

Topic 1 Statistics: An Introduction and Basic Concepts

Use of Statistics

Types of Variables

Levels of Measurement

Ethics in Statistics

Software and Statistics

Topic 2 Sampling Methods and the Central Limit Theory

Sampling a Population

Sampling Errors

Sampling Distribution of the Sample Mean

Central Limit Theorem

Topic 3 Descriptive Statistics: Numerical Measures

Arithmetic Mean

Geometric Mean

Median and Mode

Measures of Dispersion

Chebyshev's Theorem and the Empirical Rule

Using Software to Compute Descriptive Statistics

Topic 4 Descriptive Statistics: Representational

Dot Plot, Stem Plot, and Histogram

Quartiles, Deciles, and Percentiles

Skewness

Bivariate Data

Topic 5 Probability Distributions

Probability Approaches

Probability Calculations

Tools of Analysis

Computing the Number of Possible Outcomes

Topic 6 Discrete and Continuous Probability Distributions

Discrete Probability Distributions

Binomial Probability Distributions

Poisson Probability Distributions

Uniform Probability Distributions

Normal Probability Distributions

Topic 7 Using Confidence Intervals in the Sampling Process

Large Sample Confidence Intervals

Small Sample Confidence Intervals

Proportions Confidence Intervals

Sample Size

Topic 8 Regression Analysis

Correlation Analysis

Coefficient of Correlation

Regression Analysis

Confidence Interval and Prediction Intervals

ANOVA Table

Topic 9 Multiple Regression Analysis

Multiple Regression Analysis Equation

Analyzing ANOVA Table Output

Analyzing Individual Independent Variables

Topic 10 Tests of Hypothesis

Hypothesis Testing: An Introduction

Decision Making in Hypothesis Testing

Hypothesis Testing with Proportions

Two-Sample Test of Hypothesis

Topic 11 Analysis of Variance

Using the F Distribution in Variance Analysis

Analysis of Variance (ANOVA)

Computing the Analysis of Variance (ANOVA) – Sum of Squares

Analyzing the Variance

Use of Software in Variance Analysis

Topic 12 Nonparametric Methods

Chi-Square Test

Contingency Table Analysis

Sign Test

Wilcoxon Tests

Kruskal-Wallis and Spearman's Correlation Coefficient Tests

Topic 13 Time Series Forecasting

No Trend Regression Analysis

Linear Regression Analysis

Seasonal Trend Regression Analysis

Exponential Smoothing

Topic 14 Process Improvement Using Control Charts

Statistical Process Control

Creating Control Charts

Analyzing Control Charts

Natural Tolerance Limits

p Chart

Topic 15 Review

This course is designed to familiarize students with the basic concepts of business statistics and provide a comprehensive overview of the scope and limitations of statistics. Students perform statistical analysis of samples, computing the measures of location and dispersion and interpreting them through descriptive statistics. Students also perform linear regression, multiple regression, correlation analysis, model building, model diagnosis, and time series regression using various models. Basic concepts of probability are described, and the discrete and continuous distributions of probability are applied. Other topics include constructing a hypothesis, performing one-way and two-way analysis of variance, and applying nonparametric methods of statistical analysis. Making decisions under risk and under uncertainty are also examined.

After completing this course, students will be able to:- Define statistics and identify its scope and limitations.

- Describe and apply the basic concepts in statistics.

- Apply the sampling methods and the Central Limit Theorem to perform statistical analysis of samples and predict population behavior.

- Compute and interpret measures of location and dispersion.

- Represent the statistical data in different forms, and interpret the different representations.

- Perform linear regression and correlation analysis.

- Perform multiple regression and correlation analysis.

- Describe the basic concepts of probability.

- Describe and apply the discrete and continuous distributions of probability.

- Conduct hypothesis tests based on one or two samples.

- Perform one-way and two-way analysis of variance (ANOVA).

- Apply nonparametric methods of statistical analysis.

- Perform time series regression using various models.

- Perform model building and model diagnosis.

- Apply decision making theory to make decisions under risk and under uncertainty.