Answer:
a) Standard error of the mean = 1.433 mm
b) 99% confidence interval = (12.6, 22.2)
c) The precision of the estimate = 4 816
d) The assumptions that are necessary for the validity of the conidence interval constructed include
- The sample must be a random sample extracted from the population, with each variable in the sample independent from one another.
- The sample must be a normal distribution sample or approximate a normal distribution and the best way to establish this is when the population distribution where the sample was extracted from is normal or approximately normal.
Step-by-step explanation:
a) Standard error of the mean is given as
σₓ = (σ/√n)
σ = Sample standard deviation = 4.3 mm
n = sample size = 9
σₓ = (4.3/√9) = 1.433 mm
b) Confidence Interval for the population mean is basically an interval of range of values where the true population mean can be found with a certain level of confidence.
Mathematically,
Confidence Interval = (Sample mean) ± (Margin of error)
Sample Mean = 17.4 mm
Margin of Error is the width of the confidence interval about the mean.
It is given mathematically as,
Margin of Error = (Critical value) × (standard Error of the mean)
Critical value will be obtained using the t-distribution. This is because there is no information provided for the population mean and standard deviation.
To find the critical value from the t-tables, we first find the degree of freedom and the significance level.
Degree of freedom = df = n - 1 = 9 - 1 = 8.
Significance level for 99% confidence interval
(100% - 99%)/2 = 0.5% = 0.005
t (0.005, 8) = 3.36 (from the t-tables)
Standard error of the mean = 1.433 mm
99% Confidence Interval = (Sample mean) ± [(Critical value) × (standard Error of the mean)]
CI = 17.4 ± (3.36 × 1.433)
CI = 17.4 ± 4.816
99% CI = (12.584, 22.216)
One crate orė
99% Confidence interval = (12.584, 22.216)
c) The precision of the estimate is gven as the length of the, margin of error of the confidence interval. The precision of the estimate = 4.816
d) They include
- The sample must be a random sample extracted from the population, with each variable in the sample independent from one another.
- The sample must be a normal distribution sample or approximate a normal distribution and the best way to establish this is when the population distribution where the sample was extracted from is normal or approximately normal.
Hope this Helps!!!
