Exercise 31: Questions on T-Ratios

We conduct an independent sample t-test using Excel, and obtain the following output (see t-test-height)

All the p-values are greater than 0.05, therefore there is a statistical difference between each transect.

1. The researchers analyzed the data they collected as though it were at what level of measurement?- The correct answer is Interval/ratio.

1. Are any of the lab values in Table 1 out of normal range? Do you see some that are too high or too

For which of the following situations is the dependent groups t-test appropriate (if not appropriate, why?)

2. _C____ Divide your subjects in half. One group receives one treatment of the independent variable and the other group receives a different treatment of the independent variable. Subjects were all told they were going to see a video of a therapist's session after which they would rate the quality of the session. The groups differed in that the subjects in one group were told that prior evaluations indicated that the therapist was effective whereas subjects in the other group were told that the evaluations indicated the therapist was not effective. These different subjects were used for the two levels of the independent variable: subjects were in either the "effective therapist" or the "ineffective therapist" condition.

It tells that the t-statistic with 97 degrees of freedom was 2.14, and the corresponding p-value was less than .05, specifically around 0.035. Therefore, it is appropriate to conclude the research study was statistically significant.

However, treatment four, 0.1296 (±0.608), represents that the mean was extraneous from what it should be (Table 1). The t-tests show how different the mean is in each treatment.

The next table shows the results of this independent t-test. At the .05 significance level, can we conclude

We conduct an independent sample t-test using Excel, and obtain the following output (see sheet T-TEST)

With a P-value of 0.00, we have a strong level of significance. No additional information is needed to ensure that the data given is accurate.

11. t-test (p. 258) – compares the means of 2 groups – The t-test compared hyperresponsiveness and hyporesponsiveness

“Variables not in the Equation” is the title for the final table of output. The importance of this table is that it reports that the residual chi-square statistic as 26.103, which is highly significant at p < .001. The value of this statistic is that is demonstrates that the addition of

Table 1: This table summarizes the two-sample t-test analysis from SPSS of the estimated dry weight statistics at sites 1 and 2. At each site, there was a sample size of 20. The mean of

Coefficient t-Statistic Prob. Null Hypothesis Judgment LOG(CE) 0.371 3.505 0.002 Rejected Significant LOG(RE) 0.540 3.552 0.001 Rejected Significant LOG(FA) 0.138 1.577 0.126 Unable to reject Not Significant For model II, the hypothesis that the coefficient is zero is rejected at the 5% significance level only for the three of the independent variables (log(Def), log(Educ), and log(Healt)). Table 5. 15 Result of T test for Model II Variable