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🌟🌟🌟🌟🌟 Krista does a great job explaining the topics in this course. I've been looking for a course that can help me understand the Mathematics behind Machine Learning and this course fits perfectly.\n

🌟🌟🌟🌟🌟 The curriculum is comprehensive and is presented clearly and in a deliberate stepwise fashion. Ms. King is very knowledgeable and has a knack for making even complicated subjects easy to understand. She has a pleasant and friendly manner as well as a nurturing approach that helps you learn. I use all of her math courses to help tutor my daughter in her high school math subjects. You can not go wrong with any of Ms. King’s courses.\n

The curriculum includes:\n

Visualizing data\n\t
1. One-way data
2. Bar graphs and pie charts
3. Line graphs and ogives
4. Two-way data
5. Venn diagrams
6. Relative frequency tables
7. Joint distributions
8. Frequency tables and dot plots
9. Histograms and stem-and-leaf plots
Analyzing data\n\t
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2. Spread: range and IQR
3. Changing data and outliers
4. Box-and-whisker plots
Data distributions\n\t
1. Mean, variance, and standard deviation
2. Frequency histograms and polygons, and density curves
3. Symmetric and skewed distributions and outliers
4. Normal distributions and z-scores
\n\t
Probability\n\t
1. Simple probability
2. The addition rule, and union vs. intersection
3. Independent and dependent events and conditional probability
4. Bayes' theorem
Discrete random variables\n\t
1. Discrete probability
2. Transforming random variables
3. Combinations of random variables
4. Permutations and combinations
5. Binomial random variables
6. Poisson distributions
7. \"At least\" and \"at most,\" and mean, variance, and standard deviation
8. Bernoulli random variables
9. Geometric random variables
Sampling\n\t
1. Types of studies
2. Sampling and bias
3. Sampling distribution of the sample mean
4. Sampling distribution of the sample proportion
5. Confidence interval for the population mean
6. Confidence interval for the population proportion
Hypothesis testing
1. Inferential statistics and hypotheses
2. Significance level and type I and II errors
3. Test statistics for one- and two-tailed tests
4. The p-value and rejecting the null
5. Hypothesis testing for the population proportion
Regression
1. Scatterplots and regression
2. Correlation coefficient and the residual
3. Coefficient of determination and RMSE (root mean square error)
4. Chi-square tests

About the Author
\n

Krista King is a math tutor, online educator, and the creator of KristaKingMath.com. Her YouTube channel has more than 43.5 million views, and her online courses have helped more than 244,000 students.

\"Krista is very very quick to respond. I've had a few questions and I usually didn't have to wait much longer than a day to get an answer. Not only that, but she obviously spent time answering to make sure I understood the content.\" - Morgan Gray\n

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Step-by-step videos
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