Use a \( \chi^{2} \)-test to test the claim \( \sigma<44 \) at the \( \alpha=0.05 \) significance level using sample statistics \( s=40.3 \) and \( n=19 \). Assume the population is normally distributed. Identify the null and alternative hypotheses. \( \begin{array}{ll}\text { A. } H_{0}: \sigma>44 & \text { B. } H_{0}: \sigma \geq 44 \\ H_{a}: \sigma \leq 44 & H_{a}: \sigma<44 \\ \text { C. } H_{0}: \sigma \leq 44 & H_{0}: \sigma<44 \\ H_{a}: \sigma>44 & H_{a}: \sigma \geq 44\end{array} \) \( \begin{array}{ll}\text { Identify the standardized test statistic. } & \text { D. } \\ \square \text { (Round to three decimal places as needed.) } & \\ \text { Identify the critical value(s). }\end{array} \)

With \( P \)-value \( =0.000 \) and \( \alpha=0.05 \), should we reject \( H_{0} \) ? yes no

What is a scatter plot?

You run a regression analysis on a bivariate set of data ( \( n=88 \) ), You obtain the regression equation \[ y=0.231 x-8.928 \] with a correlation confficient of \( r=0.38 \) (which is significant at \( \alpha=0.01 \) ), You want to predict what value (on average) for the explanatory variable will give you a value of 90 on the response variable. What is the predicted explanatory value? \( x=\square \)

2.50. Uz jautājumu "Cik minūtes nepieciešamas, lai skolēns no mājām atnāktu uz skolu?" 60 pirmo klašu skolēnu vecāki atbildēja šādi: \( 5 ; 4 ; 28 ; 28 ; 11 ; 17 ; 17 ; 10 ; 19 ; 27 ; 22 ; 9 ; 26 ; 5 ; 19 ; 21 ; 21 ; 21 ; 7 ; 2 ; 8 ; 14 ; 5 ; 20 ; 13 ; 24 ; 14 ; 15 \); \( 3 ; 29 ; 13 ; 13 ; 22 ; 17 ; 2 ; 26 ; 30 ; 14 ; 8 ; 1 ; 20 ; 15 ; 16 ; 21 ; 20 ; 18 ; 25 ; 8 ; 12 ; 24 ; 9 ; 27 ; 8 ; 9 ; 13 ; 2 ; \) \( 8 ; 19 ; 16 ; 23 \). a) Sakārto datus tabulā, grupējot tos no 1 līdz \( 5 ; \) no 6 līdz 10; no 11 līdz 15; no 16 līdz 20; 21 un vairāk minūtes! b) Nosaki datu modu! c) Aprēkini katras datu grupas relatīvo biežumu! d) Izmantojot tabulas datus, uzzīmē relatīvo biežumu stabinu diagrammu!

Why is data collection appropriate for this two-sample proportion procedure? Because the order of applying the two treatments to each doctor was randomized in this matched pairs design. Because two separate simple random samples were taken-one from each population. Because the doctors were randomly allocated to the two treatments (aspirin and placebo).