Interpreting the resultīased on the data, conduct a hypothesis test (with a 0.05 significance level) to see if there is evidence that the population mean hours of sleep for college age students is less than the recommended 7 hours per night. This data file is stored in this location campussoftwaredeptspss and is called b4after training words.sav. Alternatively, you can divide the significance by two toĬalculate the significance of a one-tailed test (as long as your effect is in the predicted direction). See if t-obtained is larger than t-critical. Test, but if you are doing a one-tailed test, you will have to look up the t-critical yourself to The t-obtained would be the same for a one or twotailed One-Sample Test: gives your t, df, 2-tailed sig., and other stuff you don’t need to worry about. One-Sample Statistics: gives the sample size, mean and SD. The data looks fine in this problem Reading the output This can be checked with a Normal quantile plot. One sample t-test assumes that the data follow a normal distribution. The one-sample t confidence interval = (Test value + Lower, Test value + Upper).If you have a one-sided t test, your test P-value should be (Sig. To change the confidence level, you may click “Options” on the right bottom corner of the “One-Sample T Test” window and then change it. By default, it will also give you the 95% confidence interval.
Sleep deprivation can lead to decreased immune system function, lack of concentration, and poor memory. Analyzing the date with one sample t testĬollege-aged adults need at least 7 hours of sleep each night to stay healthy.You should always interpret your analysis, “How spiritual someone considers him/herself is affected by someone's belief in an afterlife. In this case, you can reject the null hypothesis (because the significance is. 05 you can reject the null (meaning there is in fact a statistically significant difference in the means and it is not due to sampling error). 05 you fail to reject the null (meaning the difference in means is likely due to chance or sampling error). A key statistic provided is the p-value, listed in the “Sig (2-tailed)” column. It is however my experience that many researchers gather data and then are at a loss for a sensible method of analysis, so Ill start by outlining the things. This table provides the test statistic or t value, the degrees of freedom and other values helpful for determining confidence intervals. 000, we'll examine the bottom row.īoth the top and bottom row provide the same information, they just use different tests to calculate the test statistic, which results in slightly different calculations. In this example, since the significance is. 05 or below, use the bottom row, or “equal variances not assumed.” If the significance is above.
By looking at the output of the Levene’s test you decide which row to use. If the variances are relatively equal, that is one sample variance is no larger than twice the size of the other, then you can assume equal variances. There is a long equation used to determine which variance to use, but SPSS does this for you by running the Levene’s Test for Equality of Variances. These group means may come from two independent samples (. Because you are comparing two means, two different variances are obtained. The T-test is used to test whether a difference between two group means is statistically significant. The second table, labeled the “Independent Samples Test,” is what you use for determining whether or not you can reject the null hypothesis. The first table is simply the “Group Statistics” table, which includes: sample sizes, means, standard deviations and standard errors of the means. A lot of information appears in these tables.