Suppose we are testing the null hypothesis H0: μ = 13 against the alternative Ha: μ < 13 from a normal population with known standard deviation σ=4. A sample of size 289 is taken. We use the usual z statistic as our test statistic. Using the sample, a z value of -2.33 is calculated. (Remember z has a standard normal distribution.) c) Would the null value have been rejected if this was a 1% level test? Yes or No d) What was the value of x calculated from our sample?
Suppose we are testing the null hypothesis H0: μ = 13 against the alternative Ha: μ < 13 from a normal population with known standard deviation σ=4. A sample of size 289 is taken. We use the usual z statistic as our test statistic. Using the sample, a z value of -2.33 is calculated. (Remember z has a standard normal distribution.) c) Would the null value have been rejected if this was a 1% level test? Yes or No d) What was the value of x calculated from our sample?
Suppose we are testing the null hypothesis H0: μ = 13 against the alternative Ha: μ < 13 from a normal population with known standard deviation σ=4. A sample of size 289 is taken. We use the usual z statistic as our test statistic. Using the sample, a z value of -2.33 is calculated. (Remember z has a standard normal distribution.) c) Would the null value have been rejected if this was a 1% level test? Yes or No d) What was the value of x calculated from our sample?
Suppose we are testing the null hypothesis H0: μ = 13 against the alternative Ha: μ < 13 from a normal population with known standard deviation σ=4. A sample of size 289 is taken. We use the usual z statistic as our test statistic. Using the sample, a z value of -2.33 is calculated. (Remember z has a standard normal distribution.)
c) Would the null value have been rejected if this was a 1% level test?
Yes or No
d) What was the value of x calculated from our sample?
Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.
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