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T - Test One - Sample Statistics table [ [ , N , Mean,Std . Deviation,Std . Error Mean ] , [ Odometer ,

T-Test
One-Sample Statistics
\table[[,N,Mean,Std. Deviation,Std. Error Mean],[Odometer,600,45237.47,32649.606,1332.915]]
One-Sample Test
Test Value =50000
\table[[,t,df,Significance,\table[[Mean],[Difference]],\table[[95% Confidence Interval of the],[Difference]]],[,One-Sided p,Two-Sided p,Lower,Upper],[Odometer,-3.573,599,.001,.001,-4762.530,-7380.28,-2144.78]]
Is there evidence that the mean PRICE of all cars is different than $13,400? Use =0.08.
Step 1: Ho: u=50000
Ha :
Step 2: Is it One sided or Two-sided?
Step 3: Find the t-test critical value
State the decision rule
Step 4: Make conclusion with the two approach
=> T-Test
Group Statistics
\table[[,Engine,N,Mean,Std. Deviation,Std. Error Mean],[Odometer,4,468,45252.67,33110.919,1530.553],[,6,132,45183.58,31080.304,2705.193]]
\table[[Independent Samples Test],[,,\table[[Levene's Test for Equality of],[Variances]],t-test for Equality of Means],[,,F,Sig.,t,df,Significance,\table[[Mean],[Difference]],\table[[Std. Error],[Difference]],\table[[95% Confidence Interval of the],[Difference]]],[,,One-Sided p,Two-Sided p,Lower,Upper],[Odometer,Equal variances assumed,1.739,.188,.021,598,.491,.983,69.085,3220.374,-6255.532,6393.703],[\table[[Equal variances not],[assumed]],,,.022,221.914,.491,.982,69.085,3108.161,-6056.203,6194.374]]
Is there evidence that the population mean ODOMETER READING of 4-cylinder cars is greater than that of 6-cylinder cars? Use =0.10.
Reject or Do not Reject?
Which equal variance will be selected?
One-sided or Two-sided? URGENR! Please answer all of the following questions. Thank you
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