Chapter 8 – Confidence Intervals, Effect
Size, and Statistical Power
Point estimate – a summary statistic from a sample that is just one number used as an estimate of the
Instead, research should be presented with interval estimates when possible
Interval estimates – based on a sample statistic and provides a range of plausible values for the
Frequently used by media, constructed by adding and subtracting a margin of error from a point
Confidence interval – is an interval estimate, based on the sample statistic, that would include the
population mean a certain percentage of the time if we sampled from the same population repeatedly.
We expect to find the population mean within a certain interval a certain percentage of the time –
Confidence interval is centered around the mean of the sample. 95% most commonly used. Indicates
the 95% that falls btwn the two tails. 100% - 5% = 95%
The confidence level is 95%, but the confidence interval is the range btwn the two values that surround
the sample mean
Steps for calculating a confidence interval:
1. Draw a pic of a distribution that will include the confidence interval
2. Indicate the bounds of the confidence interval on the drawing.
3. Determine the z statistics that fall at each line marking the middle 95%
4. Turn the z stats back into raw means
Using the mean and standard error, calculate the raw mean at each end of the confidence
interval and add them to our curve
(INSERT FORMULA BELOW)
5. Check that the confidence interval makes sense.
Sample mean should fall exactly in the middle of the two ends of the interval.
219.54 – 232 = -12.46 and 244.46 – 232 = 12.46 Confidence interval ranges from 12.46 below the sample mean to 12.46 above the sample
Can think of 12.46 as the margin of error.
the confidence interval, can be thought of as the range bounded by the sample mean plus and
minus the margin of error
Pop mean for customers at starbs that do not post calories on their menus, 247, falls outside of
this interval. Means it is not plausible that the sample of customers at starvs that post calories
on their menus comes from the pop
Data allow us to conclude that the sample comes from a diff population. We conclude that
customers at starbs that post calories on their menus consumed fewer calories than customers
at starbs that do not post calories on their menus.
Conclusions from the z tes