1 / 13

One-sample and Two-sample t-test

One-sample and Two-sample t-test. When population standard deviation (∂) is NOT KNOWN. ____. x- µ. t =. s/ √ n. When ∂ ia NOT given, we use the t-statistic. Example: performing a one-sample t-test.

apackard
Télécharger la présentation

One-sample and Two-sample t-test

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. One-sample and Two-sample t-test • When population standard deviation (∂) is NOT KNOWN

  2. ____ x- µ t = s/√n When ∂ ia NOT given, we use the t-statistic

  3. Example: performing a one-sample t-test Diet colas use artificial sweeteners to avoid sugar. These sweeteners gradually lose their sweetness over time. Manufacturers therefore test new colas for loss of sweetness before marketing them. Trained tasters sip the cola along with drinks of standard sweetness and score the cola on a “sweetness scale” of 1 to 10. The cola is then stored for a month at high temperature to imitate the effect of four months' storage at room temperature. Each taster scores the cola again after storage. Our data are the differences (score before storage minus score after storage) in the tasters' scores. The bigger these differences, the bigger the loss of sweetness. Here are the sweetness losses for a new cola, as measured by 10 trained tasters:

  4. I. Hypotheses: Ho: the mean sweetness loss is µ=0 Ha: the mean sweetness loss is positive µ>0 II. Conditions: SRS: the tasters are considered to be TRAINED so we can rely that the 10 tasters are taken from random. This is a matter of judgement Normality: the boxplot shows skewness so we will proceed with caution. Independence: since N≥100 taken from the entire population, we can view these samples as independent.

  5. 2.70 1.02 - 0 Syntax: tcdf (t-value, n, df) = t = 1.196/ 10 √ III Calculations One-sample t-test df = 9 p-value = .0123

  6. IV. Conclusion Since the p-value of .0123 is small, it gives a strong evidence against the null-hypothesis making our test significant. Therefore we have reason to believe that the mean sweetness loss is positive. However, since our sampling distribution is skewed, we will proceed with caution.

  7. Your turn! Healthy bones Here are estimates of the daily intakes of calcium (in milligrams) for an SRS of 38 women between the ages of 18 and 24 years who participated in a study of women's bone health: Suppose that the recommended daily allowance (RDA) of calcium for women in this age range is 1200 milligrams. Doctors involved in the study suspected that participating subjects had significantly lower calcium intakes than the RDA.Test the doctors' claim at the α = 0.05 significance level

  8. One-sample t-statistic: t-value = -3.95 p-value = .00017 Ho: the mean daily calcium intake is µ=1200 mg Ha: the mean daily calcium intake is µ<1200 mg SRS: taken from SRS of 29 women ages 18-24 Normality: boxplot shows distribution is skewed to the right. Independence: N≥10(39) Since our p-value is less than the 5% significance level, we will reject the null hypothesis making our test significant. Therefore the mean daily intake of calcium of women is significantly less than the RDA recommendation. However, we will proceed with caution since our distribution is skewed.

  9. Two-sample t-test We hear that listening to Mozart improves students' performance on tests. Perhaps pleasant odors have a similar effect. To test this idea, 21 subjects worked a paper-and-pencil maze while wearing a mask. The mask was either unscented or carried a floral scent. The response variable is their average time on three trials. Each subject worked the maze with both masks, in a random order. Is there an improvement in time of solving the maze with the scented mask? Carry out an appropriate test to prove this claim.

  10. Text Ho: the mean difference between wearing scented mask and unscented mask is µ=0 Ha: the mean difference between wearing scented mask and unscented mask is positive µ>0

  11. one-sample t-statistic: t-value = .349 p-value = .25 SRS: sample came from an SRS of 21 subjects Normality: The boxplot shows an approx. symmetrical distribution Independence: We are willing to assume that the 21 subjects' are independent observations. Since our p-value is greater than the 5% or even 10% significance level, we will NOT reject the null hypothesis making our test NOT significant. Therefore the floral scented mask did not help improve the average time in solving the maze.

  12. homework Right versus left: The design of controls and instruments affects how easily people can use them. A student project investigated this effect by asking 25 right-handed students to turn a knob (with their right hands) that moved an indicator by screw action in seconds.The project designers hoped to show that right-handed people find right-hand threads easier to use. Carry out a significance test at the 5% significance level to investigate this claim.

  13. Answer: Ho: the mean difference between the left hand and the right hand speed is µ=0 Ha: the mean difference between the left hand and the right hand speed is µ<0 T-value = -2.9037 P-value=.0039 Since our p-value is less than the 5% significance level, we will reject the null hypothesis making our test significant. Therefore the mean difference between the left hand the the right hand is negative. However, we will proceed with caution since our distribution is skewed.

More Related