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Prediction concerning the response Y

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Prediction concerning the response Y

- What is the mean response,E(Yh), for a given value, xh, of the predictor variable?
- What would one predict anew observation , Yh(new), to be for a given value, xh, of the predictor variable?
- What would one predict themean of m new observations, , to be for a given value, xh, of the predictor variable?

- What is the expected (mean) mortality rate for all locations at 40o N latitude?
- What is the predicted mortality rate for 1 new randomly selected location at 40o N?
- What is the predicted mortality rate for 10 new randomly selected locations at 40o N?

is the best point estimator in each case.

- That is, it is:
- the best guess of the mean response at xh
- the best guess of a new observation at xh
- the best guess of a mean of m new observations at xh

But, as always, to be confident in the answer to our research question, we should put an interval around our best guess.

Confidence interval for the population mean response E(Yh)

Formula in words:

Sample estimate ± (t-multiplier × standard error)

Formula in notation:

- The greater the spread in the xi values, the narrower the confidence interval, the more precise the prediction of E(Yh).
- Given the same set of xi values, the further xh is from the (sample) mean of the xi, the wider the confidence interval, the less precise the prediction of E(Yh).

Predicted Values for New Observations

New Fit SE Fit95.0% CI 95.0% PI

1 150.08 2.75(144.6,155.6) (111.2,188.93)

2 221.82 7.42(206.9,236.8) (180.6,263.07)X

X denotes a row with X values away from the center

Values of Predictors for New Observations

New Obs Latitude

1 40.0

2 28.0

Mean of Lat = 39.533

- xh is a value within scope of model, but it is not necessary that it is one of the x values in the data set.
- The confidence interval formula for E(Yh) works okay even if the error terms are only approximately normally distributed.
- If you have a large sample, the error terms can even deviate substantially from normality without greatly affecting appropriateness of the confidence interval.

Prediction interval for a new response Yh(new)

Formula in words:

Sample prediction ± (t-multiplier × standard error)

Formula in notation:

Assume

so

- We cannot be certain of the mean of the distribution of Y.
- Prediction limits for Yh(new) must take into account:
- variation in the possible mean of the distribution of Y
- variation in the responses Y within the probability distribution

The variation in the prediction of a new response depends on two components:

1. the variation due to estimating the mean E(Yh) with

2. the variation in Y within the probability distribution

which is estimated by:

Formula in words:

Sample prediction ± (t-multiplier × standard error)

Formula in notation:

- Stat >> Regression >> Regression …
- Specify response and predictor(s).
- Select Options…
- In “Prediction intervals for new observations” box, specify either the X value or a column name containing multiple X values.
- Specify confidence level (default is 95%).

- Click on OK. Click on OK.
- Results appear in session window.

S = 19.12 R-Sq = 68.0% R-Sq(adj)= 67.3%

Predicted Values for New Observations

New Fit SE Fit 95.0% CI 95.0% PI

1 150.08 2.75 (144.6,155.6) (111.2,188.93)

2 221.82 7.42 (206.9,236.8) (180.6,263.07)X

X denotes a row with X values away from the center

Values of Predictors for New Observations

New Obs Latitude

1 40.0

2 28.0

Mean of Lat = 39.533

- xh is a value within scope of model, but it is not necessary that it is one of the x values in the data set.
- The formula for the prediction interval depends strongly on the assumption that the error terms are normally distributed.

- Stat >> Regression >> Fitted line plot …
- Specify predictor and response.
- Under Options …
- Select Display confidence bands.
- Select Display prediction bands.
- Specify desired confidence level (95% default)

- Select OK. Select OK.