A study wants to see if a program aimed at increasing reading accuracy works for elementary school students. They have a group of 20 participants. All 20 get measured at the beginning of the study, and measured again at the completion of the reading program. This is an example of a: Within subjects study Between subjects study A correlation study A mixed design study The main difference between an ANOVA and a t-test is: Group of answer choices An ANOVA can look at more than 2, and t-test looks at only 2 means at a time An ANOVA looks at only 2 means at a time, and t-test can look at more than 2 A t-test can have nominal dependent variables An ANOVA can have a nominal dependent variable

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 + ...