Studies are often done by pha oucal companies to det errectiveness of a treat eatment program. Suppose that a new AIDS antiody drug s curmemiy un LOuy. In s give average (mean) length of time in months patients live once starting the treatment. Two researchers each follow a different set of 40 AIDS patients from the start of treatment until their deaths. The following data (in months) are collected. Researcher A 3: 4; 11: 15; 16; 17, 22: 44; 37: 16; 14; 24; 25; 15; 26; 27; 33: 29; 35: 44; 13; 21: 22; 10; 12; 8; 40; 32; 26; 27; 31; 34; 29; 17; 8; 24; 18, 47; 33: 34 Researcher B: 3: 14: 11; 5: 16; 17: 28: 41; 31; 18; 14: 14; 26; 25; 21: 22: 31; 2: 35; 44; 23; 21; 21; 16; 12; 18; 41; 22: 16; 25; 33; 34; 29; 13; 18; 24; 23: 42; 33; 29 Complete the tables using the data provided. (Enter exact numbers as integers, fractions, or decimals.) Researcher A Survival Length (in months) 0.5-6.5 Cumulative Relative Frequency Relative Frequency Frequency 6.5-12.5 12.5-18.5 18.5-24.5 24.5-30.5 30.5-36.5 36.5-42.5 42.5-48.5 Researcher B Survival Length (in months) Cumulative Relative Frequency Relative Frequency Frequency 0.5-6,5 6.5-12.5 12.5-18.5 18.5-24.5 24.5-30.5 30.5-36.5 26.5-45.5

Statistics Question

40 30 20 10 0 00 : 00000 -1.00 00000 -0.75 3. A statistics student seeking part-time employment as a New York City cab driver is trying to decide between driving a yellow cab or a green cab and examines tip amounts to help in making the decision. Using data from the New York City Taxi & Limousine Commission (http:// www.nyc.gov/html/tlc/html/about/trip_record_data.shtml), the stu- dent examines tip amounts from 25 randomly selected green cab fares and tip amounts from 25 randomly selected yellow cab fares. Graphs and summary statistics of the sample data from green cabs (G) and yellow cabs (Y) are shown. Green Cab ooooooooo000 Yellow Cab oooooooooooo 우1 -0.50 88.8. COCO 2 - 3 -0.25 4 5 Amount of Trip 0.go null = 0 Source: http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml Because each sample includes outliers, a two-sample t-test for H₁ a difference in means is not appropriate to test the hypotheses: Ho: MG My = 0, Ha:MG My # 0. The student simulates a distri- µy bution of…

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The table below shows the number of state-registered automatic weapons and the murder rate for several states in the U.S. 11.6 8.4 6.7 3.5 2.7 2.7 2.2 0.9 14.1 11.3 9.9 6.8 6.2 6.3 5.8 I = thousands of automatic weapons y = murders per 100,000 residents Keep in mind, the data in the table do not necessarily imply a direct causal link between the two variables. (In fact, can you think of any reasons why these variables may not be directly related to each other?) Also, the purpose of this question is not to make a political statement about guns or gun control. It's only to illustrate that data such as these sometimes have mathematical relationships that can be modeled with linear equations. Those relationships should always be questioned and examined carefully. With that said, these data can be modeled by the equation y = 0.87z + 3.95. Use this equation to answer the following; A) If this model is oconsistent, how many murders per 100,000 residents can be expected in a state with 8.7…

A researcher speculates that because of differences in diet, Japanese children have a lower mean blood cholesterol level than U.S. children do. Suppose that the mean level for U.S. children is known to be 175. Let ? represent the true mean blood cholesterol level for Japanese children. What hypotheses should the researcher test? H0: ? = 175 versus Ha: ? > 165H0: ? = 175 versus Ha: ? < 185     H0: ? = 175 versus Ha: ? < 175H0: ? = 175 versus Ha: ? > 175H0: ? = 185 versus Ha: ? > 175

A professor was interested in how exam performance related to study time. Just before an exam began the professor asked students in his class to write down how many hours they had studied for the exam in the past two weeks. He then compared their exam scores to the reported study time. What type of study did the professor carry out? ex post facto correlational case experimental

Check My Work (5 remaining) Each year, over 2 million people in the United States become infected with bacteria that are resistant to antibiotics. In particular, the Centers of Disease Control and Prevention has launched studies of drug-resistant gonorrhea (CDC.gov website). Of 142 cases tested in Alabama, 9 were found to be drug-resistant. Of 268 cases tested in Texas, 5 were found to be drug-resistant. Do these data suggest a statistically significant difference between the proportions of drug- resistant cases in the two states? Use a 0.02 level of significance. What is the p-value, and what is your conclusion? Test statistic = (to 2 decimals) p-value = (to 4 decimals) Conclusion: Reject the null hypothesis Choose the correct option. There is a significant difference in drug resistance between the two states. Alabama has the higher drug resistance rate. True