Social Research Methods Final Exam

Front 1

Coding

Back 1

the process of managing the data so interpretation is easier. The common coding technique is to assign numbers to the data. Spreadsheets don't like text

Front 2

Data Collection Process in 4 Steps

Back 2

1. develop a date collection form

2. designate the strategy to represent the data

3. the collection of the actual data

4. entry onto the data collection form

Front 3

Raw Data

Back 3

unorganized data

Front 4

Data Collection Form

Back 4

chart/table to represent data

1. use 1 line or row for each subject

2. use one column for each variable

3. record the subjects' id numbers as rows nd scores or other variables as columns

Front 5

Optical Scoring Sheet

Back 5

Good for collecting data where the subject's resposes are recorded as one of several options such as a multiple choice test. Use optical scanner to grade

Front 6

Getting Ready for Data Analysis

Back 6

Use descriptive statistics to describe some of the characteristics (such as the average scores of one variable) of the distribution of scores you have collected. Inferential statistics are applied to help you make decisions about how the data you collected relate to your original hypotheses and how they might be generalizable.

Front 7

Distribution of Scores

Back 7

computing a set of descriptive statistics to allw the researcher to get an accurate first impression of "what the data look like." for example, histograms.

Front 8

Summary Statistics/ Comparing Distributions of Scores- Measures of Central Tendency

Back 8

Three types of average: mean (interval and ratio data), median (ordinal data), and mode (nominal data).

Front 9

Measures of Variability/ Dispersion

Back 9

Variance (the degree of spread or dispersion that characterizes a group of scores), range (difference between highest and lowest scores), standard deviation (the average amount that each of the individual scores varies from the mean of the set of scores).

Front 10

Compute Standard Deviation

Back 10

1. list all original scores and compute mean

2. subtract mean from each individual score and place these values in a column titled "Deviations from the Mean" (next to raw score)

3. square each of the deviations and place them in a column labeled "Squared Deviations."

4. sum the squared deviations

5. divide the sum of the squared deviations by the (number of observations minus 1)

6. take the square root of last step, and that's the standard deviation :)

Front 11

Binary Variable

Back 11

yes/no, on/off

Front 12

The Normal (Bell-Shaped Curve)

Back 12

1. The mean, median and mode are all the same

2. It is symmetrical about its midpoint

3. The tails of the curve get closer and closer to the x-axis but never touch it (asymptotic)

Front 13

The Mean and the Standard Deviation of a Normal Curve

Back 13

the distance between the mean of the distribution and one unit of standard deviation to the left or the right of the mean always takes into account approximately 34% of the area beneath the normal curve, so 68% takes up one standard deviation to the left and one to the right

Front 14

Standard Scores

Back 14

scores that have the same reference point and the same standard deviation; z score is a very common standard score

Front 15

z Scores

Back 15

the result of dividing the amount that an individual score deviates from the mean by the standard deviation. should be used as the basis for comparison when scores from different distributions are being considered (or another type of standard score)

84% of the scores fall below a z score of +1.0 (the 50% that fall below the mean plus the 34% that fall between the mean, plus 1 z score.