Answer:
A sample size greater than 30
Step-by-step explanation: The central limit theorem proffers the conditions necessary to obtain a normal or bell shaped distribution. It defines normal distribution in terms of mean, standard deviation and sample size. The sample size is a very important factor in determining the shape of a distribution.
Thus with a population having mean and standard deviation stated, in other to make use of or assume normal distribution, the sample size must be large. According tho the central limit theorem, a size of greater than 30 is deemed to be large enough. As the Same size increases, the sample mean converges to the value of the population mean.
I think it’s 120. Hope this helps
Answer:
D) The z-statistics would be different.
Step-by-step explanation:
Confidence Interval can be calculated using M±ME where
- M is the sample mean
- ME is the margin of error from the mean
An margin of error (ME) from the mean can be calculated using the formula
ME=
where
- z is the corresponding z-statistic in the given confidence level
- s is the population standard deviation
If 95% and 98% confidence intervals were calculated from the same sample data, then M, s and N are same.
is called standard error. Since s and N are same the standard errors would also be same.
But, two tailed z-statistic for 95% confidence level is ≈1.96 where for 98% it is ≈2.33