estimate the simple linear regression equation.

3.5 Comparing Means from Different Populations.

3.4 Confidence Intervals for the Population Mean.

Hypothesis Testing with a Prespecified Significance Level.

Calculating the p-value When the Standard Deviation is Unknown.

Sample Variance, Sample Standard Deviation and Standard Error.

Calculating the p-Value when the Standard Deviation is Known.

3.3 Hypothesis Tests Concerning the Population Mean.

Large Sample Approximations to Sampling Distributions.

2.2 Random Sampling and the Distribution of Sample Averages.

Probability Distributions of Continuous Random Variables.

Probability Distributions of Discrete Random Variables.

2.1 Random Variables and Probability Distributions.

1.2 A Very Short Introduction to R and RStudio.

You have a set of data in Excel in front of you about sales numbers, and a scatter plot of those data points in a graphing calculator on your desk. Your boss comes by and asks you to give a regression analysis of the data by noon - he needs to know the trend line of the sales.

You rack your brain for how to find the line of best fit, remembering that it involves something with finding a straight line on a scatter plot. 3 Steps to Find the Equation for the Line of Best Fit The least squares regression is a simple linear regression analysis that is used to find the slope of the line that best fits or represents a set of data points.Ī linear equation represents the linear relationship between the x-values and y-values of the points on a graph or chart. Real-world data sets don’t have perfect or exact lines. Your job is to find an equation of a line that can represent or approximate the data. This is called the line of best fit or the regression line. You could eyeball the graph, draw a line, and pick some random numbers. Or, you could use the least squares regression to methodically figure out the line of best fit. To find the slope of our line of best fit, assemble your data into each column of a chart like the one below.

: the average value for all the x-coordinates.

Estimate the simple linear regression equation.