Stats

What does a Z score allow for?

Allows you to describe a particular score in terms of where it fits into the overall group of scores. Whether it is above or below the averag

What is a Chi-Square Test?

Evaluates whether observed frequencies for a qualitative variable (or variables) are adequately described by hypothesized or expected frequencies. Qualitative (or categorical) data is a set of observations where any single observation is a word or code that represents a class or category.

Goodness of Fit

One-Way Chi-Square - Asks whether the relative frequencies observed in the categories of a sample frequency distribution are in agreement with the relative frequencies hypothesized to be true in the population.

Explain why the mean is often not a good measure of central tendency for a skewed distribution?

With a skewed distribution, the extreme scores in the tail can influence the mean in the direction of the skew.

Under what circumstances will the mean, the median, and the mode all have the same value?

The mean , the median, and the mode will have the same value when the distribution is unimodal and symmetrical.

Under what circumstances is the mode the preferred measure of central tendency?

The mode is preferred when the scores are measured on a nominal scale.

Why would you use the mean and standard deviation together?

It is an efficient way to describe a distribution with just two numbers. And it allows a direct comparison between distributions that are on different scales

Identify the circumstances where the median instead of the mean is the preferred measure of central tendency.

The median is used instead of the mean when there is a skewed distribution (a few extreme scores), an open-ended distribution or undetermined scores.

Explain the general purpose for obtaining a measure of central tendency.

The purpose of central tendency is to find a single value that best represents an entire distribution of scores.

What are the Advantages/disadvantages of Grouping Data?

Advantages: 1.Focuses on important subpopulations and ignores irrelevant ones. 2.Improves the accuracy/efficiency of estimation. 3.Permits greater balancing of statistical power of tests of differences between strata by sampling equal numbers from strata varying widely in size. disadvantages: 1.Requires selection of relevant stratification variables which can be difficult. 2.Is not useful when there are no homogeneous subgroups. 3.Can be expensive to implement.