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summary for chp13

Course Code
Brent Berry

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Chapter 13
๎€Present data in a cross-tabulation table (it compares two nominal ordinal variables at
ounce๎€ essential for testing a hypothesis about the relationship between these two
๎€The # in a cell represents the frequency of joint occurrences of the categories of the 2
๎€Joint occurrence is the combination of categories for a single individual
๎€Colum% : is a cellโ€™s frequency as a % or the marginal total/ Row %: is a cellโ€™s frequency
as the row marginal total
๎€The existence of a relationship between two nominal ordinal variables is established
with a hypothesis test called the โ€œchi-square testโ€
๎€In a cross tab table we put the independent variable in the columns and the dependent
variable in the rows
๎€The hypothesis is stated in a way that allows us to know what sampling outcomes to
expect when hypothesise is true. With a chi-square test the hypo is stated as one of no
relationship Ho:x2 =0 or Ha:x2>0
๎€Assuming no relationship we can use the marginal frequency to predict the expected f of
each cell
๎€We compare the expected f to the observed f of each cell, and if about equal we allow
hypothesis of no relationship/ but if a large difference between expected and observed
then we expect a relationship between the variables
๎€The chi-square test tells is of the difference are so great that they are not simply the
result of sampling error
๎€Expected cell frequency: tell us how many cases should fall in a cell if each cell is
proportional to the marginal frequency
๎€E cell= (column marginal total for a cell) (row marginal total for cell)/ grand total
๎€The effect of the test is the difference between what is observed in the actual sample
data and what is hypothesise for the Ho
๎€Text statistic๎€ x2= sum (o-e)2/ e 9it measure the like hood of differences between
observed and expected cell frequencies
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