Upper limit Lower limit 9 Upper limit Lower limit 10 What is a controlling

Upper limit lower limit 9 upper limit lower limit 10

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Upper limit Lower limit
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9 Upper limit Lower limit 10 What is a controlling factor in the range of the confidence interval? Impact of sample size on size of confidence interval. N=30 N=100 Upper limit Lower limit 11 Define the Central Limit Theorem See the following video for an explanation of the Central Limit Theorem. 12 Explain the rationale for testing the difference between means. 13 Compute a z-test. Prices $ 45.23 Sample Mean $ 35.48 $ 36.57 $ 43.22 $ 42.94 $ 37.11 p-value $ 44.05 z of p-value $ 44.96 $ 42.99 $ 40.23 $ 50.93 $ 36.26 $ 51.91 $ 37.03 $ 40.12 $ 41.59 $ 40.18 $ 61.40 $ 40.51 $ 40.17 $ 49.93 $ 61.61 $ 36.93 $ 45.39 $ 41.56 $ 40.93 $ 50.49 $ 43.03 $ 40.13 $ 52.97 $ 42.10 $ 30.31 $ 54.16 $ 46.67 $ 43.32 $ 31.88 $ 64.60 $ 45.71 $ 58.27 $ 31.94 14 Compute a t-test comparing the two samples. State 1 State 2 t-Test: Two-Sample Assuming Unequal Variances 283 229 254 267 State 1 State 2 328 326 Mean 313.40625 279.625 292 309 Variance 1380.636 1196.343 Calculate a 99% confidence interval for a sample size=30 with mean of 50 and a standard deviation of 10, but the population mean and the population standard deviation are unknown . Null hypothesis (H 0 :) Alternative hypothesis (H a : ) The horizontal axis are z values. Note the small portion of the curve highlighted in blue. It's the portion of the curve that exceeds the critical value of z.
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315 231 Observations 32 40 336 283 Hypothesized Mean Difference 0 378 344 df 64 314 310 t Stat 3.95235 312 258 P(T<=t) one-tail 0.00010 328 316 t Critical one-tail 1.669013 272 241 P(T<=t) two-tail 0.000196 307 281 t Critical two-tail 1.99773 348 218 233 284 354 311 400 254 341 217 313 267 309 299 308 266 340 264 300 264 316 290 268 312 259 298 276 305 271 244 362 303 340 299 339 285 300 308 333 260 204 291 242 329 315 246 322 293 15 What is the decision rule? 16 What is statistical power? Basically is the significance level for a statistical test that is specified in advance of an analysis. Typical significance levels, called alpha levels, are .05 and .01. A difference is said to be statistically significant if a computed statistic's value exceeds the value that is expected at the significance level. The power of an hypothesis test is the probability of not making a Type II error, that is the probability of rejecting a false null hypothesis. Power varies between 0 and 1 and measures the ability of the hypothesis to detect a false null hypothesis.
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1 What's the difference in directional and non-directional hypotheses in statistical tests? 2 Compute a t-test comparing the two samples. State 1 State 2 283 229 p-value of the t-test comparing the two states, assuming unequal variances, and a one-tailed (directional) hypothesis test. 254 267 The t-value associated with the computed p-value. 328 326 292 309 315 231 336 283 378 344 314 310 312 258 328 316 272 241 307 281 348 218 233 284 354 311 400 254 341 217 313 267 309 299 308 266 340 264 300 264 316 290 268 312 259 298 276 305 271 244 362 303 340 299 339 285 300 308 333 260 204 291 242 329 315 246 322 293 3 Discuss the inpact of unequal group (sample) sizes on hypothesis tests.
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4 Use the Data Analysis t-test tool to compare the mean for Males vs. Females. Place output in J90. Male Female 4.80 4.86 3.70 2.89 3.50 4.50 3.20 3.60 3.80 3.70 4.00 4.00 4.40 3.80 3.40 4.20 4.20 2.70 3.90 2.90 3.80 3.50 4.20 3.78 3.90 3.90 4.00 4.75 3.38 3.90 4.00 3.70 3.30 3.20 3.50 2.80 3.40 4.00 3.60 3.70 3.50 3.89 3.70 3.80 4.00 4.30 3.00 2.60 4.30 4.20 4.00 3.70 2.60 4.60 3.30 4.60 4.10 3.00 3.00 4.40 3.90 2.70 4.30 3.50 3.50 4.30 3.80 3.60 3.60 3.80 3.90 4.30 4.30 4.00 3.70 3.50 3.80 4.30 3.60 4.10 4.20 3.90 3.70 3.00 3.50 3.20 3.90 2.90 3.60 3.70 3.50 4.30 4.00 4.11 4.30 2.10 4.20 3.60 3.00 3.50 3.50 3.60 4.10 3.40 4.20
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3.50 3.60 3.60 3.50 4.10 2.90 3.00 4.20 4.30 4.20 3.90 3.70 5 What is multiple gregression versus single regression?
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