Answer:
The data are at the
<u>Nominal</u> level of measurement.
The given calculation is wrong because average (mean) cannot be calculated for nominal level of measurement.
Step-by-step explanation:
The objective here is to Identify the level of measurement of the data, and explain what is wrong with the given calculation.
a)
The data are at the <u> Nominal </u> level of measurement due to the fact that it portrays the qualitative levels of naming and representing different hierarchies from 100 basketball, 200 basketball, 300 football, 400 anything else
b) We are being informed that, the average (mean) is calculated for 597 respondents and the result is 256.1.
The given calculation is wrong because average (mean) cannot be calculated for nominal level of measurement. At nominal level this type of data set do not measure at all , it is not significant to compute their average (mean).
The area of a square is equal to s^2 where s is the length of one side.
49=s^2.
Root both sides to isolate the variable.
7=s
Final answer: 7 ft
The answer would be the first one
Answer:
He could increase the sample size
Step-by-step explanation:
In hypothesis testing, the error associated with the test is affected by a number of factors. The first factor is the level of significance, alpha. This is the probability of type 1 error. The probability of rejecting the null hypothesis when it is indeed true.
The second factor is the size of the sample used. The larger the sample, the smaller the error since the characteristics of the sample will be closer to those of the entire population on which inference is being made
