Identify the regression line that best fits the data set. This video uses a very small data set to explain how to find the formula for the best-fitting line.
- The starters for a certain…men's college basketball team have the following heights…and weights.…Here's what this would look like on our scatter plot.…Now, let's find the line that best fits this data.…Remember, we're going to express the line…using the slope intercept form, y = ax + b.…In algebra, we often see slope expressed as m.…But here, we'll be using a as our slope.…B will be the y-intercept.…
You're going to want to set up six columns.…You'll then want to start to fill in your data.…Here are our given data points.…For our fourth column, (xy),…we multiply height and weight.…Our fifth column, x squared, we square our heights.…And, for our sixth column, we square our weights.…We then add up the sum of columns two through six.…
We now have everything we need.…Yes, there's a lot of calculations,…and we aren't done yet,…and this is a really small sample size.…For our example, you might be able…to do everything on a calculator.…But, when sample sizes get bigger,…you'll want to use a spreadsheet, like Excel.…In any case, most of the really hard work is done now.…
- Working with small sample sizes
- Using t-statistic vs. z-statistic
- Calculating confidence intervals with t-scores
- Comparing two populations (proportions)
- Comparing two population means
- Chi-square testing
- ANOVA testing
- Regression testing
Skill Level Advanced
1. The Statistics Series: A Look Back and Forward
2. Small Sample Sizes
T-statistic vs. z-statistic3m 44s
3. Comparing Two Populations (Proportions)
4. Comparing Two Populations (Means)
6. ANOVA: Analysis of Variance
7. Introduction to Regression
Next steps1m 40s
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