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AP Statistics5 min read

Linear Regression (LinReg) on TI-84 — AP Statistics Guide

How to calculate LinReg(ax+b) on the TI-84 Plus CE. Includes entering data in lists, running regression, interpreting r and r², and AP exam format.

Linear Regression on TI-84 — LinReg Step by Step

Enter your data, run LinReg, and get the equation ŷ = a + bx — plus r and r² — in under two minutes.


Before You Start: Turn DiagnosticOn

By default, the TI-84 hides r and r² after running LinReg. You need to enable diagnostics once, and it stays on permanently.

  1. Press 2ND0 to open the CATALOG
  2. Press D to jump to entries starting with D
  3. Scroll down to DiagnosticOn
  4. Press ENTER twice

You'll see Done on the screen. Now r and r² will always appear in your LinReg output.

This is the single most common reason students can't find r on their TI-84. Do this step first.

Step 1: Enter Your Data into Lists

  1. Press STAT1: Edit
  2. Enter your x-values in L1 (press ENTER after each)
  3. Move to L2 and enter your y-values in the same order
  4. Press 2NDMODE to quit when done

Example data (hours studied vs. exam score):

L1 (hours)L2 (score)
158
264
371
475
582
690

Step 2: Run LinReg

  1. Press STAT
  2. Arrow right to CALC
  3. Select 4: LinReg(ax+b)
  4. The command appears on the home screen: LinReg(ax+b)
  5. Press ENTER

Reading the LinReg Output

y = ax + b
a = 6.4
b = 51.2
r² = 0.994
r = 0.997
OutputWhat it meansHow to use it
a = 6.4Slope — for each 1-unit increase in x, y increases by 6.4"For each additional hour studied, the predicted score increases by 6.4 points"
b = 51.2y-intercept — predicted y when x = 0Often meaningless in context (a student can't study 0 hours) — acknowledge this
r² = 0.994Coefficient of determination — proportion of variation in y explained by x"99.4% of the variation in exam scores is explained by the linear relationship with hours studied"
r = 0.997Correlation coefficient — strength and direction of linear relationshipClose to 1 = strong positive linear association

Your regression equation: ŷ = 6.4x + 51.2

Writing the AP Statistics Regression Sentence

For the slope (most commonly tested):

"For each additional [x-unit], the predicted [y-variable] increases/decreases by [|a|] [y-units]."

For r²:

"Approximately [r² × 100]% of the variation in [y-variable] is explained by the linear relationship with [x-variable]."

For our example:

"For each additional hour studied, the predicted exam score increases by 6.4 points." "Approximately 99.4% of the variation in exam scores is explained by the linear relationship with hours studied."

Step 3: Draw the Scatter Plot and Regression Line

Set up the scatter plot:

  1. Press 2NDY= to open STAT PLOTS
  2. Select Plot1 → press ENTER
  3. Set On, Type: scatter (first icon), Xlist: L1, Ylist: L2
  4. Press ZOOM9: ZoomStat — this auto-fits the window to your data

Add the regression line:

  1. Press Y=
  2. In Y1, press VARS5: Statistics → arrow right to EQ1: RegEQ
  3. Press GRAPH

The regression line now appears over your scatter plot.

Making Predictions with the Equation

To predict y for a given x value:

Method 1 — Use the equation directly: ŷ = 6.4(4.5) + 51.2 = 28.8 + 51.2 = 80

Method 2 — Use the graph:

  1. Press TRACE
  2. Arrow right/left to move along the regression line
  3. The x and y values appear at the bottom of the screen

Extrapolation warning: Only predict within the range of your x data. Predicting outside this range (extrapolation) is unreliable — mention this on AP free response.

Common Mistakes

1. r and r² not showing up You haven't run DiagnosticOn. See the first step above — it only needs to be done once.

2. Using LinReg(a+bx) instead of LinReg(ax+b) Both calculate the same line, but the letters are swapped. LinReg(ax+b) uses a for slope and b for intercept — the AP Statistics convention. Be consistent with whichever you use.

3. Confusing r and r² r = correlation coefficient (ranges from −1 to 1, measures direction and strength). = coefficient of determination (ranges from 0 to 1, interpreted as a percentage of variation explained). They are different numbers — don't swap them in your conclusion.

4. Forgetting context in the conclusion "The slope is 6.4" gets partial credit. "For each additional hour studied, the predicted score increases by 6.4 points" gets full credit. Always include context.

Practice running LinReg on the free TI-84 calculator with your own data.

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