Connect Master for Business Statistics Online Access https://www.mheducation.com/cover-images/Jpeg_400-high/1259127680.jpeg 1 9781259127687 Connect Master Business Statistics is a digital-first product appropriate for the introductory undergraduate course. This product breaks free from the limitations and constraints of a traditional textbook’s structure and format. It uses digital adaptive software to assess how students learn, in turn providing them with an enhanced learning experience. This product is designed for instructors with technology-driven courses including hybrid, online, and those employing the flipped classroom model.
Connect Master for Business Statistics Online Access

Connect Master for Business Statistics Online Access

1st Edition
By Dane McGuckian
ISBN10: 1259127680
ISBN13: 9781259127687
Copyright: 2017
Product Details +
09781259127687

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ISBN10: 1259127680 | ISBN13: 9781259127687

1 Year

$86.00

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Program Details

Module 1: Data and the Science of Statistics
  • 1.1 The Discipline of Statistics
  • 1.2 Types of Statistics
  • 1.3 Sample Data vs. Population Data
  • 1.4 Types of Data
  • 1.5 Levels of Measurement

Module 2: Describing Attributes of a Data Set
  • 2.1 Summarizing Qualitative Data
  • 2.2 Summarizing Quantitative Data
  • 2.3 Summation Notation
  • 2.4 Measures of Center
  • 2.5 Measures of Dispersion
  • 2.6 Chebyshev's Theorem
  • 2.7 The Empirical Rule
  • 2.8 Relative Position
  • 2.9 Box Plots and Symmetry

Module 3: A Survey of Probability
  • 3.1 Basic Probability
  • 3.2 Counting Techniques
  • 3.3 Addition Rule of Probability
  • 3.4 Conditional Rule of Probability
  • 3.5 Multiplication Rule of Probability
  • 3.6 Using Complements

Module 4: Discrete Random Variables
  • 4.1 Probability Distributions for Discrete Random Variables
  • 4.2 Expected Value, Variance, and Standard Deviation for Discrete Random Variables
  • 4.3 The Binomial Probability Distribution
  • 4.4 The Poisson Probability Distribution

Module 5: Continuous Random Variables
  • 5.1 Continuous Random Variables
  • 5.2 The Normal Distribution
  • 5.3 Applications of the Normal Distribution
  • 5.4 Normal Approximation to the Binomial Distribution

Module 6: Point Estimators and the Sampling Distribution of the Sample Mean
  • 6.1 Point Estimators and Sampling Distributions
  • 6.2 The Central Limit Theorem


Module 7: Interval Estimators
  • 7.1 Interval Estimate of the Population Mean with a Known Population Standard Deviation
  • 7.2 Sample Size Requirements for Estimating the Population Mean
  • 7.3 Interval Estimate of the Population Mean with an Unknown Population Standard Deviation
  • 7.4 Interval Estimate of the Population Proportion
  • 7.5 Sample Size Requirements for Estimating the Population Proportion

Module 8: Hypothesis Testing
  • 8.1 Testing Hypothesis about a Population Mean with a Known Population Standard Deviation
  • 8.2 Testing Hypothesis about a Population Mean with an Unknown Population Standard Deviation
  • 8.3 Testing Hypothesis about a Population Proportion

Module 9: Two Sample Procedures
  • 9.1 Comparisons of Two Population Means with Known Population Standard Deviations Based on Independent Samples
  • 9.2 Comparisons of Two Population Means with Unknown Population Standard Deviations Based on Independent Samples with Equal Variances
  • 9.3 Comparisons of Two Population Means with Unknown and Assumed Unequal Population Variances Based on Independent Samples
  • 9.4 Inferences about Mean Differences (Dependent Samples)
  • 9.5 Comparisons of Two Population Proportions Based on Independent Sampling
  • 9.6 Comparisons of Two Population Variances Based on Independent Samples

Module 10: Chi-Square Procedures
  • 10.1 The Chi-Square Goodness-of-Fit Test
  • 10.2 The Chi-Square Test of Independence

Module 11: Linear Models
  • 11.1 ANOVA for Completely Randomized Design Experiments
  • 11.2 The Coefficient of Correlation
  • 11.3 Creating the Least Squares Equation
  • 11.4 Making Inference about the Slope of the Regression Line
  • 11.5 The Coefficient of Determination
  • 11.6 Confidence and Prediction Intervals for Y

About the Author

Dane McGuckian

Dane McGuckian is a Senior Statistics Instructor at Florida International University
(FIU) and the founder of STATSprofessor.com. Dane began his career as a high school
teacher at Sagemont Upper School in Weston, Florida. While in high school, Dane had no
plans to attend college and completed only the bare minimum requirements in order to
graduate. After a year-long struggle in the job market lacking a higher education, Dane
reluctantly enrolled at a local community college in Florida, Broward Community College
(BCC). There, Dane found that the discipline of mathematics was, for him, a natural fit.
Dane ended up at Florida International University where he graduated Summa Cum Laude with
a Bachelor of Science in Mathematics.

After his initial high school teaching position, Dane decided to return to the community
college where he discovered his aptitude for Mathematics as an instructor. While teaching
at BCC, Dane subsequently earned his Master of Science in Statistics from Florida
International University. Dane was hired on as an instructor at FIU in 2006.

During his first semester of teaching at FIU, Dane began independent work creating a
series of instructional videos on statistics for his students’ use. In 2011, this little
side project spun into the creation of his website, STATSprofessor.com, which is now
available to statistics students across the country.

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