INTRODUCTORY BUSINESS STATISTICS COURSE
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The Introductory Business Statistics course contains 74 self-grading microlearning lessons that work instantly inside your Learning Management System (LMS).

Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, which will serve students in their business careers and real-world experiences.

Introductory Business Statistics places a significant emphasis on the development and practical application of formulas, so that students have a deeper understanding of their interpretation and application of data. To achieve this unique approach, we’ve included a wealth of additional material and purposely deemphasized the use of the scientific calculator.

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  • Definitions of Statistics, Probability, and Key Terms
  • Data, Sampling, and Variation in Data and Sampling
  • Levels of Measurement
  • Experimental Design and Ethics
  • Final Assessment
  • Display Data
  • Measures of the Location of the Data
  • Measures of the Center of the Data
  • Sigma Notation and Calculating the Arithmetic Mean
  • Geometric Mean
  • Skewness and the Mean, Median, and Mode
  • Measures of the Spread of the Data
  • Final Assessment
  • Terminology
  • Independent and Mutually Exclusive Events
  • Two Basic Rules of Probability
  • Contingency Tables and Probability Trees
  • Venn Diagrams
  • Final Assessment
  • Hypergeometric Distribution
  • Binomial Distribution
  • Geometric Distribution
  • Poisson Distribution
  • Final Assessment
  • Properties of Continuous Probability Density Functions
  • The Uniform Distribution
  • The Exponential Distribution
  • Final Assessment
  • The Standard Normal Distribution
  • Using the Normal Distribution
  • Estimating the Binomial with the Normal Distribution
  • Final Assessment
  • The Central Limit Theorem for Sample Means
  • Using the Central Limit Theorem
  • The Central Limit Theorem for Proportions
  • Finite Population Correction Factor
  • Final Assessment
  • A Confidence Interval for a Population Standard Deviation, Known or Large Sample Size
  • A Confidence Interval for a Population Standard Deviation Unknown, Small Sample Case
  • A Confidence Interval for A Population Proportion
  • Calculating the Sample Size n: Continuous and Binary Random Variables
  • Final Assessment
  • Null and Alternative Hypotheses
  • Outcomes and the Type I and Type II Errors
  • Distribution Needed for Hypothesis Testing
  • Full Hypothesis Test Examples
  • Final Assessment
  • Comparing Two Independent Population Means
  • Cohen’s Standards for Small, Medium, and Large Effect Sizes
  • Test for Differences in Means: Assuming Equal Population Variances
  • Comparing Two Independent Population Proportions
  • Two Population Means with Known Standard Deviations
  • Matched or Paired Samples
  • Final Assessment
  • Facts About the Chi-Square Distribution
  • Test of a Single Variance
  • Goodness-of-Fit Test
  • Test of Independence
  • Test for Homogeneity
  • Comparison of the Chi-Square Tests
  • Final Assessment
  • Test of Two Variances
  • One-Way ANOVA
  • The F Distribution and the F-Ratio
  • Facts About the F Distribution
  • Final Assessment
  • The Correlation Coefficient r
  • Testing the Significance of the Correlation Coefficient
  • Linear Equations
  • The Regression Equation
  • Interpretation of Regression Coefficients: Elasticity and Logarithmic Transformation
  • Predicting with a Regression Equation
  • How to Use Microsoft Excel® for Regression Analysis
  • Final Assessment
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