This course is part of Statistics and Applied Data Analysis Specialization

Instructor: Charlie Nuttelman

What you'll learn

  •   Perform one- and two-sample hypothesis tests on the mean and variance to make statistical decisions.
  •   Create and interpret predictive regression models (linear and multiple) from experimental data.
  •   Use ANOVA (analysis of variance) to compare means of multiple samples.

    • Skills you'll gain

  •   Probability Distribution
  •   Statistical Analysis
  •   Microsoft Excel
  •   Probability & Statistics
  •   Regression Analysis
  •   Statistical Hypothesis Testing
  •   Data Analysis
  •   Sampling (Statistics)
  •   Statistical Methods

    • There are 7 modules in this course

    Statistical techniques are taught with the help of Microsoft Excel, which is an intuitive software package that has many built-in functions and tools for statistical analysis. This course is the second course out of three that comprise the specialization "Statistics and Applied Data Analysis." Course 3 ("Statistics and Data Analysis with R") focuses on statistical analysis in the statistical software package RStudio.

    Sampling Distributions and the Central Limit Theorem

    One-Sample Hypothesis Tests

    Two-Sample Hypothesis Tests

    Linear Regression

    Multilinear Regression

    ANOVA

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