And conduct a two-factor ANOVA to investigate the effects of gender (The name of the variable in SPSS is "gender" and it has two levels, "male" vs. "female") and "minority classification" (In SPSS, the name of the variable is "minority", its label is "Minority Classification" ,and it has two levels "yes" and "no"; referring to whether an individual is part of a minority or not ) on beginning salary (In SPSS the name of the variable is "salbegin", and its label is "Beginning Salary). Use α = .05a. If the main effect of Minority Classification is significant, describe the main effect of Minority Classification. Include the overall means and corresponding standard deviations in your description. Example =If there is a main effect of maternal diet, is the main effect of maternal diet significant? Why? Provide F-statistic, df of numerator, df of denominator, and p- value?Yes, the main effect of maternal diet is significant because p is less than alpha, F(1,16) = 40.67, p = .0001 Jnivariate Analysis of VarianceGenderMinority ClassificationMean画TitleStd. DeviationFemaleNoNotesLActive DatasetBetween-Subjects FactorsTests of Between-Subjects Effer513,351.22$3,064.901176Yes$11,951.25$1,928.54740Total513,091.97$2,935.599216MaleNo$21,593.81$9,677.754-ogUnivariate Analysis of Variance194Yes$16,383.7555,570.35964會TitleTotal$20,301.40$9,111.781258NotesTotalNo$17,673.0158,392.419370WarningsBetween-Subjects FactorsL Tests of Between-Subjects EfferYes$14,678.94$5,008.239104Total$17,016.09$7,870.638474LogUnivariate Analysis of VarianceTitleTests of Between-Subjects EffectsNotesDependent Variable: Beginning SalaryKO WarningsBetween-Subjects FactorsDescriptive StatisticsTests of Between-Subjects EfferType II Sumof SquaresdfMean SquareSig.SourceCorrected Model74809754883249365849653.713.000Intercept7.781E+1017.781E+101676.084.00031219088381312190883867.246.000gender849034957.118.288.000minority849034957.1282090873.76.076.014282090873.7gender* minority47046425381.872.182E+10Error4741.665E+11Total4732.930E+10Corrected Totala. R Squared = .255 (Adjusted R Squared .251)Double click to edit LogC UtilitiesExtensionsWindowOutput[自LogEUnivariate Analysis ofbecause there are fewer than three groups.會TitleNotesBetween-Subjects FactorsActive DatasetValue LabelBetween-SubjectsGenderTests of Between-fFemale216LogMale258EUnivariate Analysis of VMinority Classification0.No370會Title1Yes104NotesWarningsBetween-SubjectsTests of Between-Descriptive StatisticsLogDependent Variable: Beginning SalaryEUnivariate Analysis ofGenderMinority ClassificationMeanStd. DeviationNTitleFemaleNo$13,351.22$3,064.901176NotesYes$11,951.25$1,928.54740WarningsTotal$13,091.97$2,935.599216Between-Subjects$21,593.81$9,677.754194Descriptive StatistMaleNoTests of Between-$16,383.75$5,570.35964Yes$20,301.40$9,111.781258Total$17,673.01$8,392.419370TotalNo104$14,678.94$5,008.239Yes474$17,016.09$7,870.638Total

Question

And conduct a two-factor ANOVA to investigate the effects of gender (The name of the variable in SPSS is &#34;gender&#34; and it has two levels, &#34;male&#34; vs. &#34;female&#34;) and &#34;minority classification&#34; (In SPSS, the name of the variable is &#34;minority&#34;,  its label is &#34;Minority Classification&#34; ,and it has two levels &#34;yes&#34; and &#34;no&#34;; referring to whether an individual is part of a minority or not ) on beginning salary (In SPSS the name of the variable is &#34;salbegin&#34;, and its label is &#34;Beginning Salary). Use α = .05a. If the main effect of Minority Classification is significant, describe the main effect of  Minority Classification. Include the overall means and corresponding standard deviations in your description. Example =If there is a main effect of maternal diet, is the main effect of maternal diet significant? Why? Provide F-statistic, df of numerator, df of denominator, and p- value?Yes, the main effect of maternal diet is significant because p is less than alpha, F(1,16) = 40.67, p = .0001 Jnivariate Analysis of VarianceGenderMinority ClassificationMean画TitleStd. DeviationFemaleNoNotesLActive DatasetBetween-Subjects FactorsTests of Between-Subjects Effer513,351.22$3,064.901176Yes$11,951.25$1,928.54740Total513,091.97$2,935.599216MaleNo$21,593.81$9,677.754-ogUnivariate Analysis of Variance194Yes$16,383.7555,570.35964會TitleTotal$20,301.40$9,111.781258NotesTotalNo$17,673.0158,392.419370WarningsBetween-Subjects FactorsL Tests of Between-Subjects EfferYes$14,678.94$5,008.239104Total$17,016.09$7,870.638474LogUnivariate Analysis of VarianceTitleTests of Between-Subjects EffectsNotesDependent Variable: Beginning SalaryKO WarningsBetween-Subjects FactorsDescriptive StatisticsTests of Between-Subjects EfferType II Sumof SquaresdfMean SquareSig.SourceCorrected Model74809754883249365849653.713.000Intercept7.781E+1017.781E+101676.084.00031219088381312190883867.246.000gender849034957.118.288.000minority849034957.1282090873.76.076.014282090873.7gender* minority47046425381.872.182E+10Error4741.665E+11Total4732.930E+10Corrected Totala. R Squared = .255 (Adjusted R Squared .251)Double click to edit LogC UtilitiesExtensionsWindowOutput[自LogEUnivariate Analysis ofbecause there are fewer than three groups.會TitleNotesBetween-Subjects FactorsActive DatasetValue LabelBetween-SubjectsGenderTests of Between-fFemale216LogMale258EUnivariate Analysis of VMinority Classification0.No370會Title1Yes104NotesWarningsBetween-SubjectsTests of Between-Descriptive StatisticsLogDependent Variable: Beginning SalaryEUnivariate Analysis ofGenderMinority ClassificationMeanStd. DeviationNTitleFemaleNo$13,351.22$3,064.901176NotesYes$11,951.25$1,928.54740WarningsTotal$13,091.97$2,935.599216Between-Subjects$21,593.81$9,677.754194Descriptive StatistMaleNoTests of Between-$16,383.75$5,570.35964Yes$20,301.40$9,111.781258Total$17,673.01$8,392.419370TotalNo104$14,678.94$5,008.239Yes474$17,016.09$7,870.638Total

Accepted Answer

(a). Describe the main effect of minority classification:
The overall mean and standard deviation of…