The value of the Z statistic is 10.57 and Z obtained is 1.70, the test statistic is within the safe range, disproving the null hypothesis that there are differences in the two groups of basketball players' college preparation.
The null and alternative hypotheses are two generalizations about a population that are strictly contradictory. The null hypothesis can be denoted by H₀ and the alternative hypothesis can be denoted by H₁.
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We have the data shown in the table.
The null and alternative hypotheses are:
H0 = μ1 =μ2
H1 : μ1 > μ2
a = 0.05 (using one tailed test)
Sampling distribution = Z distribution
a = 0.05
Z(critical) = 1.65 (from the Z table)
X₁ and X₂ are sample means, S₁ and S₂ are sample standard deviations and N₁ and N₂ are the sample sizes respectively
[tex]\rm Z= \sqrt{\left(\dfrac{\left(92^2\right)}{102-1}\:+\dfrac{\left(57^2\right)}{117-1}\right)}[/tex]
= 10.57
Z(obtained) = (460 - 442)/10.57
Z(obtained) = 1.70
The test statistic is within the safe range. Therefore, disprove the null hypothesis and draw the conclusion that there are differences in the two groups of basketball players' college preparation.
Thus, the value of the Z statistic is 10.57 and Z obtained is 1.70, the test statistic is within the safe range, disproving the null hypothesis that there are differences in the two groups of basketball players' college preparation.
Learn more about the null hypothesis and alternative hypothesis here:
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