APPENDIX 1 A study examined families in three major cities in Thailand. The study focused on infant development in the context of the backgrounds and living conditions of families. 269 observations with complete observations are included in this analysis. Investigators studied predictors of infant behavioral characteristics. One of the characteristics "Excitability" was measured as the number of times an infant acted "excited" in a on hour period of time. Potential predictors included the baby's gestational age (gestation_weeks), the quality of the families living conditions (qols), mother's language-free nonverbal intelligence (TONI4_INDEX), the numbers of years of education of the father (FatherYrs Educ), the number of preterm births the mother had experienced (Preterm), and infant sex (0=female, 1=male). Below is relevant SAS Output. 0.0150 The GENMOD Procedure Model Information 0.0748 Data Set Distribution Link Function Dependent Variable WORK.ALL MERGED Poisson Log Excitability Number of Observations Read320 Number of Observations Used269 Missing Values Parameter Information ParameterEffect Prm1 Intercept Prm2 gestation_weeks Prm3 Qols Prm4 TONI4 INDEX Prm5 Father YrsEduc Prm6 Preterm Prm7 Infantsex 51 Criteria For Assessing Goodness Of Fit Criterion Deviance Scaled Deviance DF ValueValue/DF 262 577.3168 2.2035 262 577.3168 2.2035 Pearson Chi-Square Scaled Pearson X2 Log Likelihood Full Log Likelihood AIC (smaller is better) 262 566.3297 2.1616 262 566.3297 2.1616 -248.4164 -463.6072 941.2145 AICC (smaller is better) 941.6436 966.3774 BIC (smaller is better) Algorithm converged. Analysis Of Maximum Likelihood Parameter Estimates Standard Wald 95% Confidence Wald Chi- Parameter DFEstimate Error Limits Square Pr> ChiSq Intercept 1 0.2324 1.8543 -3.4020 3.8667 0.02 0.9003 gestation_weeks 1 -0.0190 0.0474 -0.1120 0.0739 0.16 0.6881 qols 1 -0.1267 0.0958 -0.3145 0.0610 1.75 0.1858 TONI4 INDEX 1 0.0034 0.0072 -0.0106 0.0174 0.22 0.6366 Father YrsEduc 1 0.0454 0.0150 0.0160 0.0748 9.14 0.0025 Preterm 1 -0.8756 0.3012 -1.4660 -0.2853 8.45 0.0036 infantsex 1 0.0712 0.1102 -0.1448 0.2871 0.42 0.5184 Scale 0 1.0000 0.0000 1.0000 1.0000 Note: The scale parameter was held fixed.

Consider the following data for this question                         B1                  B2       A1        M = 10          M = 20       A2        M = 30          M = ? The above data, what value for the missing mean would result in no interaction between A and B?     Select one: a. 20 b. 30 c. 10 d. 40

4. A study considered whether daily consumption of garlic could reduce tick bites. The study used a crossover design where half of the subjects used placebo first and garlic second and half the reverse. The authors described garlic being more effective with 58 subjects and placebo being more effective with 47 subjects. Does this suggest a real difference between garlic and placebo, or are the results consistent with random variation? Complete parts a through d below. a. Identify the relevant variable and parameter. OA. The relevant variable is the population proportion, p, those for whom garlic is more effective than placebo. The parameter is whether garlic or placebo is more effective. B. The relevant variable is whether garlic or placebo is more effective, and the parameter is the population proportion, p, those for whom placebo is more effective than garlic. C. The relevant variable is whether garlic or placebo is more effective, and the parameter is the population proportion, p,…

4. A community college wants to analyze the age and GPA of its students. Here is the data: Age 18 40 25 38 44 19 51 28 31 24 GPA 2.9 3.3 2.0 3.9 3.7 2.7 3.9 3.5 1.9 2.9 3.4 Can we say that there is a significant relationship between these variables? (Use a = %3D .05) Type of Test: Null Hypothesis: Alternate Hypothesis: SE: Test Statistic: P-value: Decision: Sentence: 21

3.  Can SAT scores predict college performance?  Let x be a variable that represents SAT score of a computer science major, and let y be a variable that represents a student’s GPA upon graduation.  A random sample of n =15 computer science majors provided their SAT scores and GPAs: x 1232 1070 1086 1287 1130 1048 1121 1095 1135 1208 1333 1160 1186 1243 1261 y 3.52 2.91 2.4 3.47 3.47 2.37 2.4 2.24 3.02 3.32 3.59 2.54 3.19 3.71 3.58   The scatter diagram for the SAT score and GPA is given below:   (a)  Find the sample correlation coefficient r.  Truncate to two decimal places.  What does the value tell you about the data? (b)  Find the equation of the least squares line .  Truncate to four decimal places.  What does the slope mean? (c)  Find the value of the coefficient of determination .  Truncate to two decimal places.  What does this number mean? (d)  What is the predicted GPA if a computer science major got a…

2. Which of the following statements defines the 97.5th percentile value for a data sample, regardless of the sample data distribution? The value that is 97.5% larger than the sample mean. The value such that 2.5% of the sample observations are larger than this value, and 97.5% of the sample observations are smaller than this value. The value such that 97.5% of the sample observations are larger than this value, and 2.5% of the sample observations are smaller than this value. This value always corresponds to the sample mean plus 2 standard deviations.

1) a.What is/are the appropriate measure(s) of central tendency for each of the variables in Columns B-F? Explain your answers in no more than two sentences each. b. Calculate the measures of central tendencies above c. Imagine that a 21st run is added to your dataset. See the table below for its data Run Eth. Gly. Acid. Temp pH 21 18.2 7.2 2.1 18 4.2 d. Do these data points change your choices of central tendency reported in Question 2b? Explain your answer.           Attached dataset;  a            b              c              d           e            f Run Ethanol Glycerol Acidity Temp pH 1 4.8 3.5 0.84 24 3.8 2 9.6 7.3 0.27 24 3.8 3 10.2 7.2 0.27 24 3.8 4 8.5 5.1 0.55 24 3.8 5 7.3 3.2 0.68 24 3.1272 6 4.8 1.2 1.24 30 4.2 7 7.9 4.4 0.65 18 3.4 8 6.7 4.3 0.65 30 3.4 9 9.8 6.9 0.47 24 3.8 10 10.2 7.2 0.32 24 3.8 11 9.8 5.8 0.51 24 3.8 12 10.2 7.5 0.28 24 3.8 13 8.2 5.1 0.49 18 4.2 14 7.1 3.9 0.6 18 3.4 15 8.2 4.8 0.46 13.908 3.8 16 5.6 3.3…

Here is the Statistics problem. Read this passage. What is the explanatory variable in this passage?

2) Researchers are interested in whether there is any relationship between a person's IQ (x- variable) and how long they live (y-variable). Answer the questions below by using the data provided. Show your work and use the back of the page if necessary. X Y 10 3 6. 6. 7 4 3 4 a) What type of statistical analysis would be most appropriate to use in this scenario? Please justify your answer. b) Please state the null and alternative hypotheses. c) Please report the results of your statistical analyses and make a decision about whether to reject or fail to reject the null hypothesis Use alpha = .05 (two-tailed). %3D

A sociologist is interested in the opinion of Minnesota teachers on the recent labor union law passed by Wisconsin lawmakers.   a. What is the experimental unit?   b.What is the population?       c.What are the variables relevant to this study? Classify them as continuous, discrete, nominal, or ordinal.       d. Explain how you would select a sample for this study. Explain pros and cons of your method.