Answer:
Yes, There is significant difference.
Step-by-step explanation:
Null Hypothesis , H0 : Mean income = 15000
Alternate Hypothesis , H1 : Mean income ≠ 15000
t = (x - u) / ( s / √n)
x = sample mean = 14500 here, u = population mean = 15000 here , s = standard deviation = 975 here , n = sample size
t = (14500 - 15000) / (975 / √169)
-500 / 75 = - 6.66
As calculated t value in absolute terms is > 1.96 , ie tabulated value at 95% significance level (two sided). So we reject the null hypothesis in favor of alternate hypothesis. Hence, we state that 'Mean Income ≠ 15000'
Probability sampling simply illustrates a scenario where the subjects of the population have an equal opportunity.
<h3>What is probability sampling?</h3>
Probability simply means the likelihood of the occurence of an event.
In this case, in probability sampling, the subjects of the population have an equal opportunity.
In non-sampling, an equal opportunity isn't given.
Learn more about probability on:
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If you have an image attached, i cant see it. Maybe just repost the question again cause i reallu cant see the attached image
Answer:
1/4
Step-by-step explanation:
-1/2 (2/2) -> -2/4
-2/4 + 3/4 = 1/4
Answer:
if 1/6 of a roll of paper covers 1/4 of a wall, this means that we will need 4/6 of a roll to cover a whole wall, now the question is asking how many rolls will we need to cover 4 walls, we already know that it takes 4/6 to fill one wall so if we add 4/6+4/6+4/6+4/6 we will get 16/6 or 2 4/6
we will need 16/6 or 2 4/6 of rolls of paper to cover 4 walls
