Answer:
The correct answer is:
if the sample size big and the sample variance is small (a)
Step-by-step explanation:
The sample size of a study is the group of subjects that are selected from the general population and is considered an accurate representation of the population. With a large sample size, the likelihood of type I and type II errors occurring reduces. Increasing sample size allows the researcher to increase the significance level of the finding because it increases accuracy in coverage of the universal set, hence the effect accurately mirrors what goes on in the whole group. However, smaller sample size, on the other hand, does not accurately mirror the whole larger group.
The sample variance is the difference between the observed value and the true(actual). It is a measure of deviation or variability between the results and the true value. A smaller variance means increase closeness to the true value hence increase in accuracy and statistical significance.
Therefore, when the treatment effect is small but the sample size is large and variance is small, then the result is statistically significant.
Answer:
The mean height is <u>69 inches</u><u><em>.</em></u>
Step-by-step explanation:
The mean or Average is a measure of the center data i.e Sum of all the observation and dividing by the total number of observation.
Here, sum of observation is equal to the sum of the heights of the players in the basketball team.
Total number of observation =10
Sum of observation=70+68+72+66+68+69+66+71+74+66=690 inches.
Therefore,the Mean Height is, 69 inches
Answer:
25
Step-by-step explanation:
The daughter is ten which means the wife is 30 (10*3) and the man is 5 years older than the wife (30+5). The man is 35 and the daughter is ten, so subtract ten years from the man (35-10) which means the man is 25 years old
The answer is three and five twelfths
3 5/12
Answer:
its 6 lbs ;)
Step-by-step explanation: