The skip interval in systematic random sampling is computed by dividing the number of potential sampling units on the list by th
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Answer:
Option B: 0.4
Step-by-step explanation:
We have 20 dots.
Such that each column represents the repetitions for each proportion.
So:
0.1 -> 3 times
0.2 -> 1 time
0.3 -> 4 times
0.4 -> 6 times
0.5 -> 3 times
0.6 -> 3 times
Now we can compute the mean of these values, and that will be the best estimation we can make with the given data.
Remember that for a set of N values:
{x₁, x₂, ..., xₙ}
The mean is:
In this case we have the set of 20 points described above, then the mean is:
Rounding to the first place after the decimal point, we get:
M = 0.4
Then the correct option is option B.
Answer:
There is sufficient statistical evidence to prove that the standard deviation of the technology-related workers and the standard deviation of the non-technology workers are equal.
Step-by-step explanation:
Here we have our null hypothesis as H₀: σ² = s²
Our alternative hypothesis is then Hₐ: σ² ≠ s²
We therefore have a two tailed test
To test the hypothesis of difference in standard deviation which is the Chi squared test given as follows
Where:
n = Size of sample
s² = Variance of sample = 950²
σ² = Variance of population = 650²
Degrees of freedom = n - 1 = 71 - 1 = 70
α = Significance level = 0.1
Therefore, we use 1 - 0.1 = 0.9
From the Chi-square table, we have the critical value as
1 - α/2 = 51.739,
α/2 = 90.531
Plugging the values in the above Chi squared test equation, we have;
Therefore, since the test value within the critical region, we do not reject the null hypothesis, hence there is sufficient statistical evidence to prove that the standard deviation of the technology-related workers and the standard deviation of the non-technology workers are equal.