t Test on SPSS
Independent and Dependent t Test on SPSS
Do the following t tests on SPSS. You have been provided with the alternative hypothesis for each question to make the writeup easier. Take the alternative hypothesis and make the necessary changes to it for the results. Do not rewrite the statement, just add the extra information as instructed. Make sure that you double space your writeup. Remove the decimals from the data. Do not round the p values from the printouts.
- How much more would you expect to pay for a home that has four bedrooms than for a home that has three? The following are asking prices for homes in a city in the Midwestern part of the United States. At α = 0.05 is there a difference in the asking prices between 3 and 4 bedroom homes?
149,900 169,900 175,000 189,000 206,900 225,000
249,900 289,900 320,000 339,900 399,900 429,900
79,500 82,000 89,999 90,000 99,900 100,000
106,900 189,900 219,900 260,000 274,900 295,900
Ha: There is a difference in asking prices between 3 and 4 bedroom homes.
- A major oil company would like to improve its tarnished image following a large oil spill. Its marketing department developed a short television commercial and tested it on a sample of 7 participants. People’s attitudes were measured with a short questionnaire, before and after viewing the commercial. At α = 0.05, did the commercial help to improve attitudes toward the oil company?
Before 15 11 10 11 14 10 11
After 15 13 18 12 16 10 19
Ha: The television commercial helped in improving attitudes toward the oil company.
*Gravetter, F. J., &Wallnau, L. B. (2005). Essentials of statistics for the behavioral sciences (5thed.). Belmont, CA: Thomson, Wadsworth.
** Moore, D. S., McCabe, G. P., & Craig, B. A. (2012). Introduction to the practice of statistics (7thed.). New York, NY: W. H. Freeman.
|Home||N||Mean||Std. Deviation||Std. Error Mean|
|Price||Four – Bedroom Homes||12||262100.00||93378.876||26956.160|
|Three – Bedroom Homes||12||157408.25||84459.912||24381.476|
|Independent Samples Test|
|Levene’s Test for Equality of Variances||t-test for Equality of Means|
|F||Sig.||t||df||Sig. (2-tailed)||Mean Difference||Std. Error Difference||95% Confidence Interval of the Difference|
|Price||Equal variances assumed||.027||.870||2.880||22||.009||104691.750||36346.815||29313.070||180070.430|
|Equal variances not assumed||2.880||21.782||.009||104691.750||36346.815||29269.296||180114.204|
|Paired Samples Statistics|
|Mean||N||Std. Deviation||Std. Error Mean|
Paired Samples Correlations
|Pair 1||Before & After||7||.167||.721|
|Paired Samples Test|
|Paired Differences||t||df||Sig. (2-tailed)|
|Mean||Std. Deviation||Std. Error Mean||95% Confidence Interval of the Difference|
|Pair 1||Before – After||-3.000||3.512||1.327||-6.248||.248||-2.260||6||.065|
- At α = 0.05, there is a statistically significant difference in the asking prices between three and four-bedroom homes in a city in the Midwestern part of the United States, with p-value of the two-tailed independent samples t-test = 0.009
- At α = 0.05, the short television commercial developed by the oil company significantly helped in improving people’s attitudes towards the oil company, with p-value of the one-tailed dependent (or paired) samples t-test = 0.0325 (0.065/2)