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Lecture 2

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University of Toronto St. George

Psychology

PSY201H1

Kristie Dukewich

Fall

Description

Lecture 2
Statistics, Sept 20
Operational definitions
When you are creating an object to measure, you want to be sure that if two people are
measuring it, they will get to the same answer
Real limits: in chapter 2
Main concepts from Pagano Chapters 3 and 4
Interpreting a whole group`s data
Frequency distribution allow us to see patterns in the data
Correlational Design
Grouped Frequency Distribution
How to define
1. Find the range of scores
Highest score – lowest score
Find range
2. Determine the interval width
Assume we want around 10 intervals
Determine i (interval width)
i = range/number of intervals
Range = 51; intervals = 10
i = 51/10
i= 5.1
You have to round it to 5, so 10 intervals each with 5 units
3. List the limits of each class interval
Begin with the lowest interval
Must contain the lowest score
Must be evenly divisible by i
4. Tally the scores
5. Obtain the Interval Frequency
3 kinds of frequency distribution:
Relative Frequency Distribution
Indicating the proportion of the total number of scores that occurs in each interval
Relative f = f/N
N= 40 (40 data points)
f= frequency distribution
Cumulative Frequency Distribution
The number of scores that fall below the upper real limit of each interval
Starting at the bottom interval add the frequency of the interval to the
frequencies of all the intervals below it
Example: If the first interval frequency is one, then add 1 to whatever the
frequency of the second interval is
Cumulate Percentage Distribution
The percentage of scores that fall below the upper real limit of each interval
Cumulative percentage = (cum f/n)100
So cumulative frequency, divide it by the # of scores, and times it by 100
They are always one or less than one!
Summarising data using graphs Vertical axis = y axis = ordinate
Frequency of scores (frequency distribution)
Plot dependent variable (results)
Horizontal axis = x axis – abscissa
Plot score values or intervals frequency distribution)
Plot levels of independent variable (experiment)
Both axes must be labeled
Both should start at 0, and if not indicate a break near the intersection
Distinguishing 4 types of graphs
Bar graphs
Nominal or ordinal scale data
Separate bar on X axis for each category or rank
Bars do NOT touch
Reflects the discrete nature of data
Histograms
When data are on an interval or ratio scale
When distance between units are constant
Separate bar drawn from x axis for each class interval
Each bar begins and ends at the real limits of the interval
The midpoint of each class interval is pl

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