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Psychology (3,337)
PSYC 1010 (57)
Chapter 2

# psych1010 chapter 2 & 3.pdf

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School
Department
Psychology
Course
PSYC 1010
Professor
Anne Bergen
Semester
Winter

Description
Psych1010 Chapter 2 & 3 notes. Chapter 2 - Frequency Distributions - Araw score is a data point that has not yet been transformed or analyzed - Afrequency distribution describes a pattern of a set of numbers by displaying a cunt or proportion for each possible value of a variable - Afrequency table is a visual depiction of data that shows how often each value occurred, that is, how man scores were at each value.Values are listed in one column, and the numbers of individuals with scores at the value are listed in the second column. - steps in creating a frequency table: - 1. determine the highest score and the lowest score. - 2. create two columns: the first is labeled with the variable name, and the second is labeled “frequency” - 3. List the full range of values that encompasses all the scores in the data set from highest to lowest. IncludeALL values in the range, even those for which the frequency is 0. - 4. Count the number of scores at each value, and write those numbers in the frequency column. - Grouped Frequency Table: a visual depiction of data that reports the frequencies within a given interval rather than the frequencies for a specific data - instead of reporting every single value in the range (like in a frequency table), we can report intervals or ranges of values. - steps in creating a grouped frequency table - 1. Find the highest and lowest scores in a frequency distribution - 2. Determine the full range of data - if there are decimal places, round both the highest and lowest scores down to the nearest whole numbers. Subtract the lowest whole number from the highest whole number and add 1 to get the full range of the data. - 3. Determine the number of intervals and the best interval size - most researchers recommend between 5 and 10 intervals, depending on the data. To find the best interval range, we divide the range by the number of intervals we want then round that answer to the nearest whole number. With wide ranges, it’s a multiple of 10 or 100, or 1000; with smaller ranges, i could be as small as 2, 3 or 5. - 4. Figure out the number that will be he bottom of the lowest interval - we want the bottom of that interval to be a multiple of our interval size. example, if we have 8 intervals of size 5, the bottom of our lowest interval should be a multiple of 5. - 5. Finish the table by listing the intervals from highest to lowest and then counting the numbers of scores in each - Histogram: looks like a bar graph but is typically used to depict scale data with the values of the variable on the x axis and the frequencies on the y-axis - each bar reflects the frequency for each value or interval - bar graphs typically provide scores for nominal data (frequencies of men and women), histograms provide frequencies for scale data (acing indices) - x-axis is horizontal __ (side to side) and the y-axis is vertical | (up&down) - steps in creating a histogram - 1. Draw the x-axis and label i with the variable of interest and the full range of values for this variable (include 0 unless all of the scores are so far from 0 that it’s impractical) - 2. Draw the y axis, label it “frequency”, and include the full range of frequencies for this variable (include 0 unless it’s impractical) - 3. Draw a bar for each value, centering the bar around that value on the x axis and drawing the bar as high as the frequency for that value as represented on the y axis Frequency Polygons - a line graph with the x axis representing values (or midpoints of intervals) and the y axis representing frequencies.Adot is placed at the frequency for each value (or midpoint), and the dots are connected. - instead of bars, we draw dots and connect them Shapes of Distribution - normal distribution: a specific frequency distribution that is a bell shaped, symmetric, unimodal curve. - Skewed distribution: distributions in which one of the tails of the distribution is pulled away from the centre. - positively skewed: the tail of the distribution extend to the right, in a positive direction - sometimes occurs when there is a floor effect: a situation in which a constraint prevents a variable from taking on values below a certain point - negatively skewed: distribution with a tail that extends to the left, in a negative direction. - sometimes a result of ceiling effect: a situation in which a constraint prevents a variable from taking on values above a given number. Chapter 3 - Visual Displays of Data Techniques for
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