# Statistics and Probability

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## Sampling from Populations

Dive into statistics with a start on data collection. Explore the differences between random sampling and a population set. Group your data and make sure you do not fall to a data error!

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## Visualizing and Exploring Different Data Types

How can data be presented meaningfully? This theme will guide you through looking at different representations of data and which would be most effective in relaying its message.

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## Describing Data

Begin using the common terminology of statistics by talking about the data using basic metrics and descriptors of the set. Learn to apply terms to discuss the variance and distribution of the data. Before moving forward, internalize the issues that plague many studies in terms of ethics when working with data.

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## Probability Theory

Revisit probability theory and its applications to statistics. Differentiate between different types of probability and the conditions that apply. Learn about the normal distribution and how a normal probability table is used.

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## Use of Probability Theory in Statistics

Use probability theory in various situations and sample sets of data to check your understanding. Apply your understanding of normal and t-distributions and also learn to apply the central limit theorem.

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## Estimation and Confidence Intervals

Learn about point and interval estimations for a sample. Apply confidence intervals and confidence levels to sample sets to describe the uncertainty of estimates.

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## Structure and Interpretation of Hypothesis Tests

Discover the importance of hypothesis tests. Define null and alternative hypotheses in various studies and then identify the appropriate test to check whether the data points towards a specific hypothesis. Apply these in several exciting case studies and test your skill.

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## Hypothesis Testing for a Single Population Mean

Apply your understanding of hypothesis testing towards a single population mean with either a known or unknown population variance. Apply the appropriate tests to check if this data supports your null hypothesis.

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## Hypothesis Testing for Two Populations

Take hypothesis testing a step further and apply in a situation concerning two independent populations. Apply the correct statistical tests and interpret the calculations to generate conclusions.

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## Analysis of Variance

Discover a new test, ANOVA, or analysis of variance. Apply these tests to population comparisons with multiple treatments or independent variables. Explore the powerful analysis that can occur with this new technique and apply it to several cases.

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## Simple Linear Regression

Explore linear regression models and how they can be applied to situations involving a constant change. Utilize all of your skills including hypothesis testing to conclude on the meaning of a data set.

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## Chi-Square Application

Explore chi-square analyses to determine if data with a categorical variable fits a hypothetical distribution. Then use the chi-square value to either prove or disprove hypotheses.

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