LSC Business Statistics (Online Course Blackboard)
1st Edition
0073341428
·
9780073341422
© 2009 | Published: April 18, 2008
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 o…
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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.
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.