She starts off with $10.25 and gets a raise of $0.50, so she earns $10.75 per hour. Then she gets a raise of 10%, so then 10.75 x 0.10 = 1.075, so she earns $11.825 per hour. Then her third raise is $0.50 so she earns $12.325 per hour. The raise for next summer is 5%, so 12.325 x 0.05 = 0.61625, so she earns $12.94125.
She will earn about $12.94 per hour starting off next summer.
Since it is observed that I z I = 3.464 > 1.96 it is concluded that the null hypothesis is rejected.
Therefore we reject John's claim.
Here:
we can use 1 sample proportion test to check the claim of John
H₀ : p₀ = 0.4
H₁ : p₀ ≠ 0.4
Test statistic is
z = p - p₀/√p₀(1-p₀)n
Let X be the random variable denoting the number of heads.
Now p = X/n
= 8/50
= 0.16
p₀ = 0.4
1-p₀ = 1-0.4
= 0.6
z = -3.464
since it is observed that I z I = 3.464 > 1.96 it is concluded that the null hypothesis is rejected.
Therefore we reject John's claim.
Learn more about Null hypothesis here:
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It’s is 997/1000. Just put the number over the highest decimal place
Answer:
$25.20
Step-by-step explanation:
First, take the 50% off the sales price:
($48)*(-0.50) = -$24.
($48 - $24) = $24 sale price.
Tax on $24 is ($24)*(0.05) = $1.20
Add the price and sales tax:
$24 + $1.20 = $25.20
Answer:
Ordinal
Step-by-step explanation:
Level of measurement used in statistics summarizes what statistical analysis that is possible. There exist three types of level of measurement. The nominal, ordinal and Interval/Ratio level of measurement. Here, our primary focus will be the Ordinal level of measurement.
Ordinal level of measurement indicates the position in a sequence. In the military sector, the officer's rank is said to be Ordinal. This implies that the ordinal level of measurement categorizes variables according to hierarchy or ranks with a meaningful order. Still, the intervals and differences between the variables may not be equal.
