Suppose M₁ and M₂ are two models where from prior knowledge we believe P(M₁) = 0.25 and P(M₂) = 0.75. We then observe a data set D. Given each model the likelihood of D is P(D|M₁) 0.5 and P(DM₂) = 0.01. Given data D which model has a higher accuracy, or probability to be correct?
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- Read through this scenario and look at the data that was collected. State the null and all possible research hypotheses. Review the results below (I used SPSS) and answer the questions that follow. Scenario: A researcher wants to see if gender and / or income affects the total amount of help given to a stranger who is sitting on the side of a busy road with a sign asking for help. The independent variables are gender, income, and the interaction of gender and income. The dependent variable is total help. He wants to know if one or both factors – or the interaction of the two - affects the total amount of help offered. Because he is analyzing two independent variables (gender and income), he used a factorial ANOVA. His results show the main effect of each of the independent variables on the dependent variable (total help) and the interaction effect. The researcher is using a 95% confidence interval which means that he wants to be at least 95% sure that his independent variables…Why is it that the correct answer is D? How can we know that the data appear to be skewed in the given problem? What are the hint words in the situation that we can say it is skewed?The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.5 8.3 6.9 3.7 2.4 2.3 2.7 0.4 yy 13.7 10.9 9.7 7 6 5.9 6.5 4.2 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.84x+3.97.y=0.84x+3.97. Use this equation to answer the following;Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 10.5 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 1 thousand automatic weapons?Answer = Round to 3 decimal places.
- The pH factor is a measurement of how acidic or alkaline water is. A reading of 7.0 indicates neutrality; values above 7.0 suggest alkalinity; and values below 7.0 indicate acidity. According to one study, the optimum likelihood of capturing bass occurs when the pH of the water is between 7.5 and 7.9. Let's say you fear acid rain is lowering the pH of your favorite fishing site, and you want to see if it's less than 7.5. You obtained 10 samples and got the following data: 7.3, 7.4, 7.2, 7.0, 7.5,7.4,7.3,7.3,7.2 and 7.1. Use 0.05 alpha. a. State the alternative and null hypothesis. b. Is the pH level of the water samples less than 7.5?A researcher hypothesizes that opera music will have an effect on test scores (but she is unsure whether they will increase or decrease). On a standardized reasoning test, known to have mu = 70 and sigma = 10, she has a sample of 30 subjects complete the test while listening to opera music. She then tallies up their scores, and finds a mean score for her sample of 66. Go through the steps of hypothesis testing and make a conclusion for the researcher about her experiment. Use a significance level of .05 (two-tailed). Sketch the chance distribution and shade your critical region.The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.5 8.4 6.9 3.9 2.7 2.8 2.2 0.6 yy 13.7 11 10 7 6.3 6.4 6.2 4.8 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation y=0.82x+4.16.y=0.82x+4.16. Use this equation to answer the following; Special Note: I suggest you verify this equation by performing linear regression on your calculator.A) How many murders per 100,000 residents can be expected in a state with 3.9 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 1.7 thousand automatic weapons?Answer = Round to 3 decimal places.
- #31). Both pictures are the same problem.Below are two boxplots. Data 1 Data 2 Based on what the boxplots show you, write True or False next to each of the following statements. 1. In Data 1, there is more data between 4 and 7 than between 2 and 4. 2. Data 2 is skewed to the left. 3. There is more variation in Data 1 than in Data 2. 4. Data 1's first quartile is equivalent to Data 2's second quartile.2) Parts A B a. b. C
- The table below shows the number of state-registered automatic weapons and the murder rate for several Northwestern states. xx 11.5 8.5 7 3.7 2.7 2.5 2.6 0.8 yy 13.8 11.1 10.1 7.2 6.4 6.1 6.1 4.8 xx = thousands of automatic weaponsyy = murders per 100,000 residentsThis data can be modeled by the equation ˆy=0.85x+4.05.y^=0.85x+4.05. Use this equation to answer the following.A) How many murders per 100,000 residents can be expected in a state with 6.7 thousand automatic weapons?Answer = Round to 3 decimal places.B) How many murders per 100,000 residents can be expected in a state with 3.3 thousand automatic weapons?Answer = Round to 3 decimal places.Chapter 11-2. The following table presents the numbers of cucumber seeds, by brand, that germinated or failed to germinate 14 days after planting. Brand A Brand B Brand C Brand D 27 Germinated 28 33 36 Failed to Germinate 5 17 4 5 Can you conclude that the the germination rate is related to the brand of seed? Use the a = 0.05 level of significance. Reject Ho. It appears that the germination rates differ among the seed brands. Do not reject Ho. There is insufficient evidence to conclude that the germination rate differs among the seed brands.Suppose the observational units in a study are the patients arriving at an emergency room on a given day, 11 Nov 2019. For the following indicate whether it can legitimately be considered a variable or not: Whether or not men have to wait longer than women yes no
