Chapter 8 stats.docx

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Psychology 2135A/B
Sandra Hessels

Chapter 8 – Confidence Intervals, Effect Size, and Statistical Power Confidence Intervals Point estimate – a summary statistic from a sample that is just one number used as an estimate of the population parameter. Instead, research should be presented with interval estimates when possible Interval Estimates Interval estimates – based on a sample statistic and provides a range of plausible values for the population parameter. Frequently used by media, constructed by adding and subtracting a margin of error from a point estimate 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 – usually 95% 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 mean. 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
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