Introduction to the Course
  • Introduction and Data Files to Download
Introduction to Statistics, Data and Statistical Thinking
  • Statistics, Data and Statistical Thinking
Managing Data in a Minitab Worksheet
  • Getting Started with Minitab
  • Summarizing Cases, Row Statistics
  • Summarizing Columns, Using Session Commands
  • Coding Data
  • Ranking and Sorting of Data
  • Standardizing Data
  • Creating Subsets of Worksheet
  • Combining Data using the Stack Option
  • Separating Data using the Unstack Option
Descriptive Statistics - Data Analysis For One Variable - Qualitative Data
  • Describing Qualitative Data
  • Numerically Summarizing Qualitative Variables
  • Creating Bar Charts
  • Creating Pie Charts
  • Test Yourself - Questions
  • Test Yourself - Answers
Descriptive Statistics - Data Analysis For One Variable - Quantitative Data
  • Numerical Measures of Central Tendency
  • Numerical Measures of Variability
  • Using the Mean and Standard Deviation to Describe Data
  • Numerical Measures of Relative Standing
  • Numerically Summarizing Quantitative Variables
  • Graphical Methods for Describing Quantitative Data
  • Creating Histograms
  • Creating Stem-and-Leaf Displays
  • Creating Dotplots and Individual Value Plots
  • Methods for Detecting Outliers: Box Plots and z-scores
  • Creating Boxplots
  • Distorting the Truth with Descriptive Techniques
  • Test Yourself - Questions
  • Test Yourself - Answers
Descriptive Statistics - Data Analysis for Comparing Groups
  • Contingency Tables
  • Cluster and Stack Bar Charts
  • Comparing Subgroups by Dotplots and Individual Value Plots or Boxplots
  • Comparing Subgroups Numerically
  • Using Charts to Display Descriptive Statistics
Descriptive Statisitcs - Relationships Between Two Quantitative Variables
  • Bivariate Relationships
  • Creating Scatterplots
  • Adding a Grouping Variable to a Scatterplot
  • Creating Marginal Plots
  • Computing Covariance and Correlation
  • Computing and Displaying the Regression Line
  • Test Yourself - Questions
  • Test Yourself - Answers
Probability
  • Events, Probability, and Sample Spaces
  • Unions and Intersections
  • Complementary Events
  • Conditional Probability
  • The Additive Rule and Mutually Exclusive Events
  • The Multiplicative Rule and Independent Events
  • Bayes's Rule
  • Test Yourself - Questions
  • Test Yourself - Answers
Random Variables and Probability Distributions
  • Two Types of Random Variables
  • Probability Distributions for Discrete Random Variables
  • The Binomial Distributions
  • Other Discrete Distributions: Geometric, Poisson and Hypergeometric
  • Calculating Individual and Cumulative Probability for the Binomial Distribution
  • Calculating Individual Cumulative and Inverse Cumulative Poisson Probability
  • Probability Distributions for Continuous Random Variables
  • The Normal Distribution
  • Descriptive Methods for Assessing Normality
  • Other Continuous Distributions: Uniform and Exponential
  • Calculating Porbablities Using Distribution Plots
  • Calculating Critical Values of Random Variables using Distribution Plots
  • Test Yourself - Questions
  • Test Yourself - Answers
Random Data - Sampling Distributions
  • The Concept of Sampling Distributions
  • Properties of Sampling Distributions: Unbiasedness and Minimum Variance
  • Generating Random Data From Normal Distribution and Checking Normality
  • Sampling from a Column
  • Simulating Sampling with More Samples, Sampling Error
  • Simulation Technique to Study Distributions of Sample Statistics
  • The Sampling Distribution of a Sample Mean and the Central Limit Theorem
  • Distribution of the Sample Mean. Known and Unknown Variance.
  • The Sampling Distribution of the Sample Proportion and Sample Variance
  • Distribution of the Sample Proportions. Large and Small Sample.
  • Distribution of Sample Variances. Normal Population. Large and Small Sample.
  • Test Yourself - Questions
  • Test Yourself - Answers
Inferences From One Sample - Estimation with Confidence Intervals
  • Identifying and Estimating the Target Parameter
  • Confidence Interval for a Population Mean: Normal (z) Statistic
  • Confidence Interval for a Population Mean: Student’s t-Statistic
  • Large-Sample Confidence Interval for a Population Proportion
  • Confidence Interval for a Population Variance
  • Finite Population Correction for Simple Random Sample
  • Simulation of Confidence Intervals for the Mean of a Normal Population
  • Simulation of Confidence Intervals for the Mean. Unknown Variance
  • Determining the Sample Size