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22 Cards in this Set
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 Back
What is the primary purpose of descriptive statistics?

The primary goal is to bring order out of chaos. To help resolve problems by making it possible to summarize and describe large quantities of data.


What are the most useful types of descriptive statistics?

Frequency Distributions and graphs, measures of central tendency, measures of variability, transormed scores, areas under the curve.


Frequence Distributions and Graphs

Procedures for describing all (or nearly all) of teh data in a convenient way.


Measures of "Central Tendency"

single numbers that describe the location of a distribution of scores: where the "center of gravity" of scores generally falls within the infinite range of possible values.


Measures of variability

Single numbers that describe how"spread out" a set of scores are: whether the numbers are similar to each other and vary very little, as opposed to whether they tend to be very different from one another and vary a great deal.


Transformed Scores

New socres that replace each original number, and show at a glance how good or bad any socre is in comparioson to the other scores in the group.


Area under the normal curve.

proportions that tell you the probability of randomly selecting a score smaller or larger than yours from a particular normal distribution.


What is a regular frequency distribution, how is it constructed, and why is it useful?

A more comprehensible way of recording the data. The first step is to list every score value in the first column of a table with the highest score at the top. The frequency is listed to the right of the score in the second column. To arrive at the figures in the "Frequency" column, you go through the data and count all the numbers and make a mark in the appropriate row. It makes it easier to interpret the scores since you can conveniently ascertain information.


How does a cumulative frequency distribution differ from a regular frequency distribution, and how is it constructed?

The difference is there an addiction column of information containing the cumulative frequency until that current interval. It is constructed in the same way besides the additional column that records the cumulative frequency.


How does a grouped frequency distribution differ from a regular frequency distribution, and how is constructed?

When there are 15 or 20 values of X this method is used instead. Instead of having a single score in the score column, there is an interval listed instead. It is constructed in a similar manner to the RGD however the intervals are decided by three steps:
1. Have a total approximately 8 to 15 class intervals. 2. Use an interval size of 2,3 or 5(multiple of 5) selecting the smallest size that will satisfy the first rule. 3. Make the lowest score in each interval a multiple of the interval size. 

What is gained by using a grouped frequency distribution?

It still keeps enough information to give a quality summary of the data however it is excellent way to summarize a column that is too large to write completely out.


What is lost by using a grouped frequency distribution, and why are such distributions usually not used when computed means and other statistics?

Their is information lost whe the data is grouped since there will be no data on each particular score making it hard to interpret the data. That is why there should not be statistics computed from this data because there is too much data missing to compute an accurate statistic.


What are bar charts, histograms, frequency polygons and stemandleaf displays?

Effective ways of representing frequency distributions pictorially as well as in tables.


When is a bar chart preferable to a histogram?

When there is discrete data, and between scores cannot occur. Categorial data and noncontinous data.


When is a frequency polygon preferable to a histogram?

When there is multiple distributions that you want to show on one chart, as well as when there are many different scores to be compariing.


What is meant when we say that a distribution is symmetric?

If it can be divided into two halves.


Skewed?

A asymmetric distribution with a pronounced tail.


Unimodal?

On the graph there is only one peak in the data.


Bimodal?

There is two clearly pronounced peaks.


Normal?

Bellshaped, symmetric and unimodal distribution.


Rectangular?

Each score occurs with the same frequency.


JCurve?

The Lowest score is the most frequent and the frequencies decrease as teh scores become larger.
