Statistics Videos

Statistics Unit 1: Introduction to Data Statistics

Statistics Unit 3: Displaying & Summarizing Quantitative Data

Statistics Unit 2: Displaying & Describing Categorical Data

-What is Statistics?-

-Contextualizing Data-

-Categorical versus Quantitative Variables-

Statistics Unit 2: Displaying & Describing Categorical Data

Statistics Unit 3: Displaying & Summarizing Quantitative Data

Statistics Unit 2: Displaying & Describing Categorical Data

-Frequency and Relative Frequency Tables-

-Drawing and Interpreting Pie Charts-

-Drawing and Interpreting Bar Graphs-

-Working with Contingency Tables-

-Drawing Side by Side Bar Graphs-

-Interpreting Contingency Tables-

Statistics Unit 3: Displaying & Summarizing Quantitative Data

Statistics Unit 3: Displaying & Summarizing Quantitative Data

Statistics Unit 3: Displaying & Summarizing Quantitative Data

-Drawing & Understanding Histograms-

-How to Make a Stem and Leaf Display-

-Shape of a Distribution-

-Finding a Median-

-5 Number Summary, Range & Interquartile Range-

-Introduction to Outliers-

-Finding the Mean-

-Finding the Standard Deviation-

-Finding the Measures of Central Tendency and Quartiles for a List Using the TI-84-

-Finding the Measures of Central Tendency and Quartiles for a Table Using the TI-84-

Statistics Unit 4: Comparing Distributions

Statistics Unit 5: Using Standard Deviation as the Ruler / The Normal Model

Statistics Unit 3: Displaying & Summarizing Quantitative Data

-Box and Whisker Plot with No Outliers-

-Determining an Outlier Using the 1.5 IQR Rule-

-Box and Whisker Plot with Outliers-

-Matching Histograms with Box Plots-

-Comparing Box Plots-

Statistics Unit 5: Using Standard Deviation as the Ruler / The Normal Model

Statistics Unit 5: Using Standard Deviation as the Ruler / The Normal Model

Statistics Unit 5: Using Standard Deviation as the Ruler / The Normal Model

-Standardizing Values by Finding Z-Scores-

-The Normal Model and the 68-95-98.7 Rule-

-Finding Normal Percentiles Using a Z Score Table-

-Using NormalCDF in the TI 84 to Find Probability-

-Using INVNorm in the TI 84-

Statistics Unit 6: Scatter Plots, Association, and Correlation

Statistics Unit 5: Using Standard Deviation as the Ruler / The Normal Model

Statistics Unit 5: Using Standard Deviation as the Ruler / The Normal Model

-Scatter Plots, Association, and Correlation-

-An Introduction to the Correlation Coefficient-

-Finding the Correlation Coefficient and Line of Best Fit Using the TI-84-

-Calculating the Correlation Coefficient and Best Fit Regression Using Google Sheets-

-Linear Regression-

-Assumptions and Conditions for Regression-

Statistics Unit 7: Understanding Randomness

Statistics Unit 9: Experiments & Observational Studies

Statistics Unit 7: Understanding Randomness

-What is a Simulation?-

-Designing a Simulation-

-Designing a Simulation Involving Probability-

Statistics Unit 8: Sample Surveys

Statistics Unit 9: Experiments & Observational Studies

Statistics Unit 7: Understanding Randomness

-Survey Sampling Methods-

-Top 10 Tips for Survey Writing-

Statistics Unit 9: Experiments & Observational Studies

Statistics Unit 9: Experiments & Observational Studies

Statistics Unit 9: Experiments & Observational Studies

-Observational Studies versus Experiments-

-Statistics Experiments-

Statistics Unit 10: Randomness & Probability

Statistics Unit 11: Sampling Distribution Models

Statistics Unit 9: Experiments & Observational Studies

-Introduction to Probability-

-Law of Large Numbers-

-Addition Rule of Probability-

-The Multiplication Rule of Probability-

-Mutually Exclusive Events-

-Introduction to Conditional Probability-

Probability with Tree Diagrams-

-Conditional Probability and Tree Diagrams-

Statistics Unit 11: Sampling Distribution Models

Statistics Unit 11: Sampling Distribution Models

Statistics Unit 11: Sampling Distribution Models

-The Central Limit Theorem for Sample Proportions-

-Conditions for the Central Limit Theorem for Sample Proportions-

-The Central Limit Theorem for Sample Means-

-Confidence Intervals for Population Proportions-

Statistics Unit 12: Hypothesis Testing

Statistics Unit 11: Sampling Distribution Models

Statistics Unit 11: Sampling Distribution Models

-Video Coming Soon-