Question 1. a) Consider an experiment which measures the value of three different vari - ables on a unit. This experiment was conducted twice, giving two samples (both with 22 observations each), with...

Needed to be solve part B correctly in 10 minutes and get thumb up please show neat and clean workQuestion 1. a) Consider an experiment which measures the value of three different vari -<br>ables on a unit. This experiment was conducted twice, giving two samples (both with<br>22 observations each), with sample means<br>s-) -()<br>0.<br>1<br>1<br>and sample covariance matrices<br>-() -C)<br>20 1<br>-4 0 -1<br>0 2 0<br>-1 0 3<br>S1 =<br>030<br>S2 =<br>1 0 5<br>i) Calculate the pooled sample covariance Spl for this data;<br>ii) Calculate the corresponding Hotelling's T2-statistic and thus, conclude if the null<br>hypothesis Ho should be rejected at the 1% significance level by comparison to a<br>critical value from an F-table.<br>b) If the null hypothesis in the two-sample T2-test is rejected, i.e. the two population means<br>are not equal, we can determine which variable contributed the most to this rejection by<br>finding the linear transformation coefficient vector ā, which maximises the T-statistic<br>T = -<br>ni + n2<br>nin2<br>where Spi is the pooled sample covariance. It can be shown that the coefficient vector<br>the so-called 'discriminant function'<br>which maximises this statistic<br>

Extracted text: Question 1. a) Consider an experiment which measures the value of three different vari - ables on a unit. This experiment was conducted twice, giving two samples (both with 22 observations each), with sample means s-) -() 0. 1 1 and sample covariance matrices -() -C) 20 1 -4 0 -1 0 2 0 -1 0 3 S1 = 030 S2 = 1 0 5 i) Calculate the pooled sample covariance Spl for this data; ii) Calculate the corresponding Hotelling's T2-statistic and thus, conclude if the null hypothesis Ho should be rejected at the 1% significance level by comparison to a critical value from an F-table. b) If the null hypothesis in the two-sample T2-test is rejected, i.e. the two population means are not equal, we can determine which variable contributed the most to this rejection by finding the linear transformation coefficient vector ā, which maximises the T-statistic T = - ni + n2 nin2 where Spi is the pooled sample covariance. It can be shown that the coefficient vector the so-called 'discriminant function' which maximises this statistic "s ä = S' (j1 – J2) . Using the discriminant function, show that the square of the maximised T-statistic is nothing other than the original Hotelling's T2 statistic for two samples, i.e. -1 T² = (ñn – 72)" ( (- 1 Spl n2 (51 – 52). n1

Jun 07, 2022
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