Chapter 2: Norms and Statistics Flashcards
What are the properties of scales that make scales different from one another?
- Magnitude (the “moreness”)
- Equal Intervals (point between one and two is the same between two and three)
- Absolute Zero (if we have zero of this it is meaningful)
- Discrete vs Continuous (values can be divided)
Know the four scales of measurement and be able to differentiate between these scales
Nominal
- Values symbolize a category
- No calculation
Ordinal
- Names for these but the categories have magnitude
- No calculation
Interval
- Equal intervals for each part
- You can do calculations with these
Ratio
- There is a true zero with equal intervals
- Calculable
- We can create ratios because we know where to start
- Can create a ratio with these values
Think of concrete examples of each of the different scales of measurement.
Nominal: gender
Ordinal: ranks in the military
Interval: Celsius or Fahrenheit
Ratio: Kelvin
Define frequency distribution and histogram? What kind of data are shown in each?
Frequency distribution: how often each different value in a set of data occurs
histogram: shows frequency distribution
Discrete or continuous data that is measured on an interval scale
Understand the concept of percentiles.
Ex: The 75th percentile is the value at which 25% of the answers lie above that value and 75% of the answers lie below that value.
Define central tendency. Know the three types of central tendency and how to calculate each.
a single value that attempts to describe a set of data by identifying the central position within that set of data.
Mean, mode, median
Define variance and standard deviation.
Variance - averaged squared deviations around the mean, “the spread”
Standard deviation - positive square root of the variance, Gives a useful approximation of how much a typical score is above or below the average score
Understand Normal Distribution conceptually.
The normal distribution is a continuous probability distribution that is symmetrical around its mean, most of the observations cluster around the central peak, and the probabilities for values further away from the mean taper off equally in both directions
Define skewness and be able to identify positive and negative skew.
a distortion or asymmetry that deviates from the symmetrical bell curve, or normal distribution, in a set of data
Define kurtosis
how peaked is the data
What is a z score? How is it calculated?
the number of standard deviations a given data point lies above or below mean
Purpose: show how far a score falls from the mean z=(x- average)/sd
How are T scores different from Z scores?
Z score: population raw data or more than 30 data
T score: from the sample data of less than 30 data to a standard score
What are quartiles? What is Interquartile range?
each of four equal groups into which a population can be divided according to the distribution of values of a particular variable.
IQR: measures the spread of the middle half of your data
Define norm, norming, and standardization. For what is each used?
Norm: how your scores compare to a group on a test, standardized score. Think ACT
Norming: process of creating a norm
Standardization: specific procedures for administration, the scoring, and the interpretation. Every test, test-taker, and scoring is the same, reduces error
To avoid bias, how should error be distributed in a psychological test?
randomly distributed
