people who were playing roulette is 55.5 with a standard deviation of 3.2 years. Can it be concluded at =α0.10 that the mean age of those playing the slot machines is less than those playing roulette? Use μ1 or the mean age of those playing slot machines. Assume the variables are normally distributed and the variances are unequal. ind the critical value(s). Round the answer(s) to at least three decimal places. If there is more than one critical value, separate them with commas. Critical Value(s): Compute the test value. z
people who were playing roulette is 55.5 with a standard deviation of 3.2 years. Can it be concluded at =α0.10 that the mean age of those playing the slot machines is less than those playing roulette? Use μ1 or the mean age of those playing slot machines. Assume the variables are normally distributed and the variances are unequal. ind the critical value(s). Round the answer(s) to at least three decimal places. If there is more than one critical value, separate them with commas. Critical Value(s): Compute the test value. z
Ages of Gamblers The mean age of a sample of 25 people who were playing the slot machines is 49.9 years, and the standard deviation is 6.8 years. The mean age of a sample of 33 people who were playing roulette is 55.5 with a standard deviation of 3.2 years. Can it be concluded at =α0.10 that the mean age of those playing the slot machines is less than those playing roulette? Use μ1 or the mean age of those playing slot machines. Assume the variables are normally distributed and the variances are unequal.
ind the critical value(s). Round the answer(s) to at least three decimal places. If there is more than one critical value, separate them with commas.
Critical Value(s):
Compute the test value. z=
Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...
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