The alpha level that a researcher sets at the beginning of the experiment is the level to which he wishes to limit the probability of making the error of . Identify the boundaries that separate the extreme samples from the samples that are more obviously consistent with the null hypothesis. Assume the null hypothesis is nondirectional, meaning that the critical region is split across both tails of the distribution. The z-score boundaries at an alpha level α = .05 are:

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Step-by-step explanation:

The alpha level set at the beginning of of an experiment is used by the researcher to the limit the probability if making a type 1 error. The type 1 error is committed when a true null hypothesis is incorrectly rejected.

The type 2 error on the other hand is committed when fail to reject a false null hypothesis.

Hence, in other to forestall the risk of incorrectly rejecting a true null hypothesis, the alpha level is set.

When critical region is split across both tails of the distribution, The z-score boundaries at an alpha level α = .05

α = .05 (95% confidence level)

When region is split into 2:

α/2 = .05/2

α/2 = 0.025

Loooking up the z table for the Zscore with probability of 0.025

Zscore = ±1.96

change of stock price/initial stock price on friday * total stock value = change of stock value

0.89/73.73 *x = 42.72

x=3539.04 = total stock value at initial stock price on friday .

total stock value at initial stock price on friday/ initial stock price on friday = number of shares

3539.04/73.73 = 48 shares

they own 48 shares of this stock

160 cm

step-by-step explanation:

you have to add all the sides together