8. Testing for Differences in Means and Proportions: Paired Samples t-test
Paired Samples t-test: Test Statistic and p-value
The government of Canada wants to know whether the legalization of marihuana has had any effect on the rate of drug-related offenses. To investigate this matter, a researcher selects a simple random sample of #14# cities and compares the rates of drug-related offenses before #(X)# and after #(Y)# the legalization was implemented.
The values in the table below are the number of drug-related offenses per #100#,#000# residents:
City | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 |
#X:\,\text{Before}# | 239 | 248 | 236 | 228 | 238 | 234 | 253 | 252 | 261 | 224 | 269 | 252 | 268 | 226 |
#Y:\,\text{After}# | 240 | 243 | 225 | 226 | 235 | 229 | 249 | 251 | 262 | 222 | 271 | 249 | 262 | 220 |
You may assume that the population distributions of drug-related offenses both before and after the legalization are normal.
The researcher plans on using a paired samples #t#-test to determine whether the legalization of marihuana has had a significant effect on the number of drug-related offenses.
Define #D=X-Y#.
State the null and alternative hypotheses of the proposed test.
#H_0 : \mu_D\,\,#
#H_a : \mu_D\,\,#
#H_a : \mu_D\,\,#
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