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  3. Inferential Statistics
  • 1

    The Basics of R

    This lab is about teaching enough R to start using it for statistical analyses.

  • 2

    Introduction to R continued

    This lab continues with an introduction to R

  • 3

    Comparing two groups

    The current lab treats differences between two independent groups, paired groups and proportions

  • 4

    Categorical Association

    Investigating associations between categorical variables.

  • 5

    Simple Regression

    Predicting a response variable one predictor variable.

  • 6

    Multiple Regression

    Predicting a response variable with more than one predictor variable.

  • 7

    Quantitative associations: ANOVA

    This lab treats the statistical methodology of the analysis of variance

  • 8

    Nonparametric tests

    This lab will treat testing methods that can be employed when the assumptions of other methods are not met

Initializing

Exercise

Finding the Slope and Intercept Using lm()

So you conducted your experiment when you gave people money and measured how much they like you. You calculated the slope and the intercept manually, so that you have the equation \(liking = 1.501 + 0.778 * money\).

Another way of calculating the intercept and slope is through the R function lm(). When you tell lm() your regression model, it produces your intercept and slope coefficients. You give lm() your model by first specifying the y (or response) variable, followed by a ~ symbol, then your x (or predictor variable). For example: lm(y~x). Try it for yourself in your script!

Instructions

100 XP
  • In your script, add a line of code that calculates the intercept and slope using lm()
  • Hit 'submit' and look at the answer!