Which variable age or sex has a higher proportional reduction of error? a. Not assuming the null hypothesis.b. Using the asymptotic standard error assuming the null hypothesis.We take another look at the frequency of political discussions (DISCPOL), first presented inTable 10.11 (based on GSS 2014). DISCPOL is presented with two independent variables-12.sex and (2) age (measured in categories as reported in corresponding tables).(1) respondentInterpret each measure of association. Which variable-age or sex-has a higher propor-tional reduction of error?Countdiscpol HOWOFTEN R DISCUSSPOLITICSTotaldiscpol HOW OFTEN R DISCUSS POLITICS RAge recoded Age CrosstabulationRAge recoded Age2.00 30-39 3.00 40-49 4.00 50-59Count1 OFTEN2 SOMETIMES3 RARELY4 NEVERdiscpol HOWOFTEN R DISCUSSPOLITICSTotalGamma1.00 18-29312191852Symmetric MeasuresAsymptoticStandardizedErrorValue-.206260Ordinal byOrdinalN of Valid Casesa. Not assuming the null hypothesis.b. Using the asymptotic standard error assuming the null hypothesis.1 OFTEN2 SOMETIMES3 RARELY4 NEVER.070discpol HOW OFTEN R DISCUSS POLITICS sex RESPONDENTS SEXCrosstabulationApproximateTD21$74932159517253178sex RESPONDENTS SEX1 MALE2 FEMALE-2.93214498264209Total3510613196368416231558ApproximateSignificance.003826241472Total20719178260CHAPTER 10 The Chi-Square Test and Measures of Association Nominal byNominalLambdaGoodman andKruskal tauGenderMaleFemaleTotalSymmetricdiscpol HOWOFTEN R DISCUSSPOLITICSDependentsexDirectional MeasuresIndigenous statusNonindigenousIndigenousRESPONDENTSSEX Dependentdiscpol HOWOFTEN R DISCUSSPOLITICSDependentsexRESPONDENTSSEX DependentValue.058.034a. Not assuming the null hypothesis.b. Using the asymptotic standard error assuming the null hypothesis.C. Based on chi-square approximation.0941,146 (88.29)156 (81.68)1,302.013815 (87.17)477 (88.17).039Violent Offense Onset by Gender, Race, and AgeAsymptoticStandardizedError.047.043.071.007.020ApproximateTb1.213.778152 (11.71)35 (18.32)1871.26613. Paul Mazerolle, Alex Piquero, and Robert Brame (2010) examined whether violent onsetoffenders have distinct career dimensions from offenders whose initial offending involves non-violence. In this table, the researchers investigate the relationship between gender, race, andage, and nonviolent versus violent onset using chi-square analysis. Their data are based on 1,503juvenile offenders in Queensland, Australia. The independent variables are reported in rows.120 (12.83)ApproximateSignificanceThe chi-square models for gender and age at first offense are significant at the .01 level. Interpretthe relationship between gender and age at first offense with a nonviolent or violent initial offense..225.437206.003Nonviolent Onset N (%) | Violent Onset N (%) |_ Total N (%).0021,298 (100)191 (100)1,489x²=6.331**935 (100)41 (100)

Proportional reduction of error (PRE) is the measure of the extent by which one variable can help us…

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A patient is classified as having gestational diabetes if their average glucose level is above 140 milligrams per deciliter (mg/dl) one hour after a sugary drink is ingested. Rebecca's doctor is concerned that she may suffer from gestational diabetes. There is variation both in the actual glucose level and in the blood test that measures the level. Rebecca's measured glucose level one hour after ingesting the sugary drink varies according to the Normal distribution with μ=140+5 mg/dl and σ=5+1 mg/dl. Using the Central Limit Theorem, determine the probability of Rebecca being diagnosed with gestational diabetes if her glucose level is measured: Once? n=5+2 times n=5+4 times Comment on the relationship between the probabilities observed in (a), (b), and (c). Explain, using concepts from lecture why this occurs and what it means in context.
The slope of a regression line tells you how much or little a change in your dependent variable impacts your independent variable. O TrueO False
For a sample of 41 California cities, a sociologist studies the crime rate in each city (crimes per 100,000 residents) as a function of its poverty rate (in %) and its median income (in $1,000s). The sociologist finds that SSE = 4,182,663 and SST= 7,732,451. Round all answers to 4 decimal places. What is the standard error of the estimate? What proportion of the sample variation in crime rate is explained by variability in the predictor variables? What proportion is unexplained?
Ocean currents are important in studies of climate change, as well as ecology studies of dispersal of plankton. Drift bottles are used to study ocean currents in the Pacific near Hawaii, the Solomon Islands, New Guinea, and other islands. Let x represent the number of days to recovery of a drift bottle after release and y represent the distance from point of release to point of recovery in km/100. The following data are representative of one study using drift bottles to study ocean currents. 203 x days y km/100 72 76 32 14.7 94 11.7 19.5 5.3 35.6 (a) Verify that Ex = 477, Ey = 86.8, Ex? = 62,029, Ey2 = 2028.68, Exy = 11036.6, and r= 0.93853. Ex Ey Ex? Ey2| Exy (b) Use a 1% level of significance to test the claim p> 0. (Use 2 decimal places.) critical t Conclusion Reject the null hypothesis, there is sufficient evidence that p > 0. Reject the null hypothesis, there is insufficient evidence that p > 0. O Fail to reject the null hypothesis, there is insufficient evidence that p > 0. O…
Why is the coefficient of variation important? What do we mean when we say that the coefficient of variation has no units? What advantage can there be in having no units? Why is relative size important?
Can you solve for the p-value and is H0 rejected or not rejected?
Range of ankle motion is a contributing factor to falls among the elderly. Suppose a team of researchers is studying how compression hosiery, typical shoes, and medical shoes affect range of ankle motion. In particular, note the variables Barefoot and Footwear2. Barefoot represents a subject's range of ankle motion (in degrees) while barefoot, and Footwear2 represents their range of ankle motion (in degrees) while wearing medical shoes. Use this data and your preferred software to calculate the equation of the least-squares linear regression line to predict a subject's range of ankle motion while wearing medical shoes, ?̂ , based on their range of ankle motion while barefoot, ? . Round your coefficients to two decimal places of precision. ?̂ = A physical therapist determines that her patient Jan has a range of ankle motion of 7.26°7.26° while barefoot. Predict Jan's range of ankle motion while wearing medical shoes, ?̂ . Round your answer to two decimal places. ?̂ = Suppose Jan's…
What is the variable requirement for a chi-square analysis?

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