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Lecture Description
I introduce log transformations and show how to make curved exponential data linear so that we can analyze the data with a linear regression line. Part 2 is transforming data that follows a power function.
Course Index
- Stem Plots in Statistics
- Histograms in Statistics
- Making histograms, boxplots,and timeplots with a graphing calculator
- Catagorical Graphs in Statistics
- Describing Distributions in Statistics
- Determining Skewness In Ogive Graphs
- Resistance, Mean, Median, 5 Number Summary and BoxPlots
- Standard Deviation Preview and IQR Test
- Distribution Shapes, Ogive Graphs, and Time Plots
- Standard Deviation and Linear Transformations
- Density Curves, Empirical Rule & Normality, Z-score Intro
- Normal Probability Plots & the TI-84
- z-score Calculations & Percentiles in a Normal Distribution
- TI-NSPIRE Z score to Pval & Pval to Zscore NormCDF invNorm
- Scatter Plot Intro and Lurking Variables defined
- Intro of Corellation "r" to measure linear strength
- Outlier vs Influential Point
- Regression lines, Residual plots, and Correlation with TI-NSpire
- Least Squares Regression Line Notes
- Regression Lines and Correlation with TI-84
- Log Transformation Part 1
- Log Transformations Part 2
- Log Transformations with a TI-NSPIRE
- Histogram, Boxplot, Dot Plot, & Normal Prob Plot on TI-NSPIRE
- Scatter Plot, Linear Reg, Correlation & Residuals with TI-NSPIRE
- Log Transformations with TI-84
- Simpson's Paradox
- Relationship between catagorical variables in a 2 way table
- Log Tranformation with TI-NSPIRE
- Causation Defined & 5 Key Checks for Signs of Causattion
- Sampling Techniques Part 1
- Sampling Techniques Part 2
- Cautions about Sample Surveys, Causes of Bias, and Inference defined
- Sampling Techniques & Cautions (Full Length)
- Experimental Design Part 1
- Experimental Design Part 2
- Simulation Notes for Statistics
- Intro to Probabilities in Statistics (Full Length)
- Intro to Probabilities Part 1
- Intro to Probabilities Part 2
- Intro to Probabilities Part 3
- General Probability Rules (Full Length)
- General Probability Rules Part 2
- General Probability Rules Part 1
- Discrete & Continuous Random Variables (Full Length)
- Discrete & Continuous Variables Part 1
- Discrete & Continuous Variables Part 2
- TI-NSPIRE Discrete Random Variable Mean & Standard Deviation
- Combining Means and Variance in Statistics
- Combining Means and Variance Examples
- Binomial Setting & Binomial Distribution in Statistics Pt 1
- Binomial Setting & Binomial Distribution in Statistics Pt 2
- Geometric Setting & Distribution in Statistics
- Calculating 1-Var Statistics with a TI-NSPIRE
- Intro to Sample Mean Distribution and Central Limit Theorem
- 1 Sample Mean Z-Test Example
- Introduction of Sample Proportions
- Example of 1 Sample Proportion Z-test
- N-SPIRE 1 Proportion Z-Test Example
- Intro to Confidence Intervals & 1 Sample Mean z Interval
- 1 Sample Mean t-Confidence Interval
- Matched Pairs t Confidence Interval
- 1 Sample Proportion z Confidence Interval
- Significance Hypothesis Test Intro & Matched Pairs t-Test
- 2 Sided Hypothesis Tests & Confidence Intervals
- Type 1 Error Type 2 Error Power 1 Sample Mean Hypothesis z-Test
- Power of a T Test 1 Sample Mean
- Power 1 Sample Proportion z-Test (2 Sided)
- 2 Sample Mean t-test & Confidence Interval
- 2 Sample Mean Hypothesis t Test & Confidence Interval Example w/ TI-NSPIRE
- 2 Proportions Pooled Hypothesis z-test & Confidence Intervals
- Chi Square Goodness of Fit Test
- TI-NSPIRE Chi Square Goodness of Fit Test
- Chi Square Test for Independence & Homogeneity
- TI-NSPIRE Chi Square Test on 2 Way Tables
- Chi Square Calculation by Hand
- Linear Regression t test and Confidence Interval Corrected
- Linear Regression t test and Confidence Interval
- TI-NSPIRE Linear Regression t-test & Confidence Interval of slope
Course Description
In this series, the very helpful and fun math teacher Mr. Rob Tarrou teaches students everything they need to know to get a 5/5 on their AP Statistics exam by the College Board. His videos are friendly, easy to understand, entertaining, and very well organized, all thanks to Mr. Tarrou great dedication to teaching and enthusiasm for mathematics
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