SMSU General Psychology students were asked to complete a section of the Anders Child Rearing Attitude Scale dealing with their attitudes about child rearing during infancy and the early childhood years. Scores obtained on the Anders Scale can range from -19 to +22 , with lower scores representing more restrictive attitudes about child rearing and higher scores representing more permissive attitudes. Scores on this scale, as well as some demographic information (sex and age), were analyzed with SPSS. An independent samples t-test was used to determine whether male and female students differed in their attitudes toward child-rearing. The results are below. Group Statistics \begin{tabular}{ll|l|r|r|r} & sex of respondent & \( N \) & Mean & Std. Deviation & Std. Error Mean \\ \hline \begin{tabular}{l} Child Rearing Attitude \\ Score \end{tabular} & male & 27 & 7.07 & 4.402 & .847 \\ \hline & female & 29 & 7.86 & 5.383 & 1.000 \\ \hline \end{tabular} Independent Samples Test \begin{tabular}{|c|c|c|c|c|c|c|c|c|} \hline & & \begin{tabular}{l} vene's \\ vality of \end{tabular} & \begin{tabular}{l} st for \\ riances \end{tabular} & & & & 1-test & or Equality o \\ \hline & & & & & & Signifi & cance & \\ \hline & & \( \mathrm{F} \) & Sig. & \( \mathrm{t} \) & df & One-Sided p & Two-Sided p & Difference \\ \hline \begin{tabular}{l} Child Rearing \\ Attitude Score \end{tabular} & \begin{tabular}{l} Equal variances \\ assumed \end{tabular} & .742 & .393 & -.597 & 54 & .276 & .553 & -78 \\ \hline & \begin{tabular}{l} Equal variances \\ not assumed \end{tabular} & & & -.601 & 53.142 & .275 & .550 & \\ \hline & & & epender & it Samp & les Effe & ct Sizes & & \\ \hline & & & & & & & \( 95 \% \) Confiden & e Interval \\ \hline & & & & Stan & ardicer \( ^{2} \) & Point Estimate & Lower & Upper \\ \hline & Child Rearing Attitude & Coh & & & 4.935 & -.160 & -.684 & .366 \\ \hline & Sco & & s' correctio & & 5.005 & -.157 & .674 & .361 \\ \hline & & Gla: & 5 delta & & 5.383 &,- 146 & -.671 & .380 \\ \hline \end{tabular} a. The denominator used in estimating the effect sizes.
Added by Amber P.
Close
Step 1
In simpler terms, it checks if different groups have similar levels of variance on the measured variable, which is a key assumption for conducting an independent samples t-test. Show more…
Show all steps
Your feedback will help us improve your experience
Audrey Fong and 54 other Intro Stats / AP Statistics educators are ready to help you.
Ask a new question
Labs
Want to see this concept in action?
Explore this concept interactively to see how it behaves as you change inputs.
Key Concepts
Recommended Videos
Q1. Explain inter-item reliability analysis (Cronbach' alpha) in the context of the MMPI -2 displayed in the table below. - (A) What is the purpose of inter-item reliability analysis? - (B) Explain why low inter-item reliability occurs. - (C) Explain why high inter-item reliability emerges. - (D) Overall, is the MMPI-2 a reliable measure? Why? - (E) To what extent does gender influence the reliability of MMPI-2? TABLE Q1 T-score means, standard deviations, and alpha coefficients for the MMPI-2 Restructured Clinical scales and non-K-corrected Clinical scales. Men Scale M (SD) ̑ RCd (dem) 65.0 (14.8) .94 RC1 (som) 62.2 (16.5) .88 RC2 (lpe) 58.7 (14.6) .83 RC3 (cyn) 56.7 (12.7) .85 RC4 (asb) 63.6 (14.3) .85 RC6 (per) 63.3 (14.0) .85 RC7 (dne) 59.9 (15.1) .90 RC8 (abx) 59.3 (15.7) .87 RC9 (hpm) 52.5 (12.1) .83 1 (Hs) 61.8 (15.8) .90 2 (D) 66.9 (15.2) .82 3 (Hy) 60.2 (15.1) .70 4 (Pd) 70.5 (14.5) .76 6 (Pa) 67.8 (18.6) .71 7 (Pt) 63.9 (16.4) .94 8 (Sc) 66.1 (18.0) .94 9 (Ma) 58.4 (13.8) .67 Women Scale M (SD) ̑ RCd (dem) 64.8 (13.8) .94 RC1 (som) 63.2 (14.3) .87 RC2 (lpe) 64.1 (16.9) .84 RC3 (cyn) 56.8 (12.8) .86 RC4 (asb) 61.1 (13.5) .83 RC6 (per) 63.8 (14.7) .84 RC7 (dne) 60.2 (13.9) .89 RC8 (abx) 59.7 (14.8) .84 RC9 (hpm) 51.6 (12.0) .82 1 (Hs) 63.9 (14.5) .89 2 (D) 70.5 (17.7) .84 3 (Hy) 64.3 (16.1) .73 4 (Pd) 70.1 (14.9) .76 6 (Pa) 68.5 (18.3) .71 7 (Pt) 65.1 (15.3) .94 8 (Sc) 67.6 (17.2) .94 9 (Ma) 57.1 (12.7) .66 Note. MMPI-2 = Minnesota Multiphasic Personality Inventory-2; dem = Demoralization; som = Somatic Complaints; lpe = Low Positive Emotions; cyn = Cynicism; asb = Antisocial Behavior; per = Ideas of Persecution; dne = Dysfunctional Negative Emotions; abx = Aberrant Experiences; hpm = Hypomanic Activation; Hs = Hypochondriasis; D = Depression; Hy = Hysteria; Pd = Psychopathic Deviate; Pa = Paranoia; Pt = Psychasthenia; Sc = Schizophrenia; Ma = Hypomania. an = 280. bn = 264. Original article: Handel RW, Archer RP. An investigation of the psychometric properties of the MMPI-2 Restructured Clinical (RC) scales with mental health inpatients. J Pers Assess. 2008 May;90(3):239-49. doi: 10.1080/00223890701884954. PMID: 18444120.
Samriddhi S.
Suzanne Zeedyk, a developmental psychologist at Dundee University's School of Psychology, conducted a pilot study in which parents started a half-hour walk with their infants in a parent-facing or an away-facing stroller and then switched to the other type of stroller midway. Her results suggest that parents talked less to the babies, the babies had higher heart rates, and they were less likely to fall asleep in away-facing strollers than in parent-facing strollers. You are interested in testing the hypothesis that babies who travel in parent-facing strollers have different expressive vocabularies than babies who travel in away-facing strollers. You randomly assign 18 newborns to parent-facing strollers and 18 newborns to away-facing strollers. You then test the babies' expressive vocabularies at age 36 months using the Expressive Vocabulary Test (EVT), which is designed primarily to assess children's expressive vocabulary. The sample means and sums of squares of the scores for each of the groups are presented in the following table. Group Sample Mean Sum of Squares Away-facing 92.7 2,828.97 Parent-facing 104.3 2,530.28 You decide to use an ANOVA at α = 0.05 to test the null hypothesis that there is no difference between the groups. The ANOVA table follows. Calculate the F-ratio and enter it into the table. Source of Variation ANOVA Table Sum of Squares Degrees of Freedom Mean Square F Between Treatments 1,211.04 1 1,211.04 Within Treatments 5,359.25 34 157.63 Total 6,570.29 35 Use the Distributions tool that follows to find Fcritical at a significance level of α = 0.05, the value of F that bounds the critical region for the F-ratio test statistic. (Note: Do not use the t-tables. In some cases, when the degrees of freedom are not exact, they do not provide answers with enough precision for this exercise.) F Distribution Numerator Degrees of Freedom = 26 Denominator Degrees of Freedom = 26 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 0.00 F 0.5000 0.5000 1.000 Fcritical at α = 0.05 is . Now evaluate the null hypothesis that the population means for all treatments are equal. At a significance level of α = 0.05, the null hypothesis is . You find that you conclude that the direction that the stroller faces influences a child's expressive vocabulary at 36 months. Now you decide to use a t test to test the hypothesis that there is no difference between the groups. The estimated standard error (sM1 - M2) is 4.19, so the t test statistic is . Use the following tool to find the critical regions for α = 0.05. t Distribution Degrees of Freedom = 21 -3.0 -2.0 -1.0 0.01 0.02 0.03 3.0 t 0.2500 0.5000 0.2500 0.5000 0.5000 -0.686 0.686 0.000 The critical t-scores (the values for t-scores that separate the tails from the main body of the distribution, forming the critical regions) are . Now use the tool to evaluate the null hypothesis. At a significance level of α = 0.05, the null hypothesis is . You find that you conclude that the direction the stroller faces influences a child's expressive vocabulary at 36 months. When you evaluated the mean difference from the independent-measures study comparing only two samples, the ANOVA and the t test resulted in conclusion.
Luke H.
You have a sample of 25 cities, chosen randomly from the population of all cities in the US over 1,000 people. The mean rate of compliance with a federal regulation on water use in these 25 cities is 76.3%. It is known from previous studies that this compliance has a national standard deviation of 8.4%, and we can assume that it is the same in this present study. a. (2 points) Calculate the interval around your sample mean that you are 90% confident that it contains the population mean. Note: you should be using the t-distribution. b. (2 points) Given the scenario in a., that is, a sample of 25 cities, a mean rate of compliance of 76.3%, and a national standard deviation of 8.4%, calculate the 90% confidence interval using the z-distribution instead. c. (1 point) Compare your results from a. and b.. What differences did you find? 3. You have a set of climate data for Miami, FL, including monthly temperatures, rainfall, snowfall, and several other variables, for the last 30 years. Over those years, the mean July temperature has been 33.5 degrees C. Since records began in Miami (assume n to be large), the mean July temperature has been 31.7 degrees with a standard deviation of 5.3 degrees. You will consider the 30-year-record as "representative" if the sample mean is not significantly different (at a 95% confidence level) than the population mean. This is a two-tailed test. a. (0.5 point) What is the null hypothesis H0 here? b. (0.5 point) What is the alternative hypothesis HA? c. (2 points) Find the 95% confidence interval (CI) around the sample mean. d. (1 point) Does the population mean fall inside the 95% CI? What does it mean if it does or does not? e. (1 point) Based on the same overall scenario, state a research question and a null and alternative hypothesis that would require a one-tailed test. f. (2 points) Determine the 95% confidence region for the one-tailed scenario.
Madhur L.
Recommended Textbooks
Elementary Statistics a Step by Step Approach
The Practice of Statistics for AP
Introductory Statistics
Watch the video solution with this free unlock.
EMAIL
PASSWORD