A line of best fit is a line that follows the pattern of the data. It goes through or close to as many of the data values as possible.

For each line of best fit there are confidence values for how accurately the line matches the data. There are 4 main confidence values:

No correlation Weak Strong Very Strong

In addition to confidence values for the line of best fit on a scatter plot we also have what is called correlation values. The correlation is the direction of the slope:

Practice: Tell what confidence and correlation the scatter plots have.

1. 2.

Review writing equations of linear lines

Remember Linear Lines mean straight lines

The basic formula for all linear lines is y=mx+b

m=slope and b=y-intercept

There are 3 main ways to find slope:

1. Counting from a graph. Always read a graph

From left to right (just like a book).

2. Formula:

3. Solving an equation for y=mx+b form (we will look at this method more in depth soon).

Practice: Finding slope

1)

4)

Warm-up

Create a box and whisker plot for the following set of data:

86, 98, 73, 75, 23, 81, 60, 89, 93, 82

20 30 40 50 60 70 80 90 100

Using lines of best fit to predict or project what will happen if the trend of the line continues.

1. Draw the line of best fit

2. What type of correlation and how strong

is it?

3. Given the equation y=5x +60 predict

Predict the grade for someone who studies

For 6 hours.

4. What do the slope (5/1) and y-int (60)

Mean in terms of the problem?

5. Is there any correlation between

The number of hours studied and the

Grade on the final exam?

1 2 3 4 5 6 60

65

70

75

80

85

90

95

Hours Studied

Gra

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