Suppose 2 docoss A and B test all into patients coming for syphilis. Let At ={ doctor Á makes a a clinic pesitive diagnosis} and Bt = { docbr B makes a postive diagnosis} %3D Suppose doctor A A diagnoses 10%% of all patients as postive, positive and both as docfor B diaanoser 17% of all patients
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- A new screening test for Lyme disease is developed for use in the general population. The sensitivity and specificity of the new test are 60% and 70%, respectively. Five hundred people are screened at a clinic during the first year the new test is implemented. Assume the true prevalence of Lyme disease among clinic attendees is 10%. Calculate the predictive value of a positive test.A research team is interested in investigating the effectiveness of a new medication intended to reduce resting heart rate (beats per minute, BPM) in overweight patients. In order to test the medication, the researcher organizes a clinical trial with participants randomly assigned to receive either the new medication or a placebo. Suppose the following table represents the heart rates for a SRS from both groups. Data for the placebo group are {71, 71, 68, 67, 68, 69, 70, 70, 69, 72, 73} Data for the treatment group are {67, 66, 64, 64, 65, 64, 59, 63, 71, 64} Sample standard deviation for the placebo group is: 1.834 Sample standard deviation for the treatment group is: 3.057 What is the confidence interval? (alpha=0.05) Group of answer choices (0.969492 to 9.266508) (2.31312 to 7.92288) (2.598132 to 7.637868) (-1.796934 to 12.032934)You are interested in understanding the impact of Student Teacher Ratios (STR) on Test Scores (i.e., STR is your variable of interest and Test Scores are your outcome variable). Let’s pretend you have 2 models and you must only pick 1. The models along with mock results are in the table below. The coefficients are presented with standard errors in parenthesis. Further assume that the STR coefficient in Model 1 is less biased than the STR coefficient in Model 2. But as you can see, the STR coefficient in Model 2 is more precisely estimated (it’s statistically significant) than the coefficient in Model 1. Which model (Model 1 or Model 2) do you prefer and why. X1 and X2 are different control variables. You do not need to know what they are in order to answer this question – you only need to know that they are different. Y = Test Scores Model 1 Model 2 STR -1.4 (0.9) -3.7** (0.9) X1 5.6** (2.2) X2 4.6** (2.1) Constant 680*** (45)…
- Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables margin, - the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and • home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: regress margin home if team===== "Brooklyn Nets" . Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1459.95122 1 80 190.65061 None of the above 81 206.320988 Coef. Std. Err. 8.439024 3.049595 -5.219512 2.156389 MS t Number of obs F(1, 80) Prob > F R-squared O The Nets lost more games than they won in 2014 P>|t| 2.77 0.007 -2.42 0.018 Adj R-squared = Root…A research team is interested in investigating the effectiveness of a new medication intended to reduce resting heart rate (beats per minute, BPM) in overweight patients. In order to test the medication, the researcher organizes a clinical trial with participants randomly assigned to receive either the new medication or a placebo. Suppose the following table represents the heart rates for a SRS from both groups. Data for the placebo group are {71, 71, 68, 67, 68, 69, 70, 70, 69, 72, 73} Data for the treatment group are {67, 66, 64, 64, 65, 64, 59, 63, 71, 64} Sample standard deviation for the placebo group is: 1.834 Sample standard deviation for the treatment group is: 3.057 What is the Standard Error of the Mean Difference? (alpha=0.05) Group of answer choices 1.834 1.240 1.114 3.057A research team is interested in investigating the effectiveness of a new medication intended to reduce resting heart rate (beats per minute, BPM) in overweight patients. In order to test the medication, the researcher organizes a clinical trial with participants randomly assigned to receive either the new medication or a placebo. Suppose the following table represents the heart rates for a SRS from both groups. Data for the placebo group are {71, 71, 68, 67, 68, 69, 70, 70, 69, 72, 73} Data for the treatment group are {67, 66, 64, 64, 65, 64, 59, 63, 71, 64} Sample standard deviation for the placebo group is: 1.834 Sample standard deviation for the treatment group is: 3.057 What is the test statistics (tstat)? (alpha=0.05) Group of answer choices 4.127 2.791 1.674 4.594
- A police academy has just brought in a batch of new recruits. All recruits are given an aptitude test and a fitness test. Suppose a researcher wants to know if there is a significant difference in aptitude scores based on a recruits’ fitness level. Recruits are ranked on a scale of 1 – 3 for fitness (1 = lowest fitness category, 3 = highest fitness category). Using “ApScore” as your dependent variable and “FitGroup” as your independent variable, conduct a One-Way, Between Subjects, ANOVA, at α = 0.05, to see if there is a significant difference on the aptitude test between fitness groups. Identify the correct symbolic notation for the alternative hypothesis. A. H0: µ1 = µ2 B. HA: µ1 ≠ µ2 ≠ µ3 C. H0: µ1 = µ2 = µ3 D. HA: µ1 ≠ µ2In 2004 it was reported that 31% of all graduating US college students were graduating with STEM degrees (Science Technology Engineering and Math). You want to study if this percentage has increased. To study this you divide the country into 4 major regions, East Coast, Midwest, South, and West Coast and randomly sample 70 students from each region. This means you ultimately randomly sample 280 graduating students and find that 95 of them were graduating with STEM degrees. (a) Carry out at α = .05 a hypothesis test to test the claim that the percentage of US college students that get STEM degrees has increased since 2004. Make sure to check all necessary condi- tions and state your conclusion in the context of this problem. (b) Build a 95% confidence interval to estimate the current percentage of US college students that graduate with a STEM degree. Make sure to check any necessary conditions and interpret your interval in the context of this problem. (c) What type of sampling did you…Consider data on every game played by the Brooklyn Nets in 2014 (82 games) that includes the variables margin; - the Net's margin of victory (number of points the Nets scored minus the number of points their opponent scored) for game i, and • home; - a dummy variable equal to 1 when the Nets are the home team (game i was played in their home arena) and equal to 0 when they are the away team (game i was played in the opponent's arena). I use the least-squares method to estimate the following regression model margin = a + ßhome; + ei Below is the Stata output corresponding to the estimated regression line: regress margin home if team==== "Brooklyn Nets" Source Model Residual Total margin home _cons SS 1459.95122 15252.0488 16712 df 1 80 Coef. Std. Err. MS 81 206.320988 8.439024 3.049595 -5.219512 2.156389 1459.95122 190.65061 t Number of obs F (1, 80) Prob > F R-squared. Adj R-squared = Root MSE P>|t| 2.77 0.007 -2.42 0.018 82 7.66 0.0070 0.0874 0.0760 13.808 [95% Conf. Interval]…
- why is the DV female drosophila Do you use a z or test for this problem?Suppose you have a survey where one of the variables is "Sex", and all of the 300 people surveyed answered one of the following: 1) Male or 2) Female. Suppose further that you create 2 dummy variables: D1 = 1 if male, zero otherwise D2 = 1 if female, zero otherwise What would happen if you include both dummy variables in your regression in Excel? O Excel will not be able to run a regression with both variables in the regression. Nothing. This is the correct way to do it. O Your regression will exhibit serial correlation. O Your regression will exhibit some multicollinearity, but can be remedied with "robust standard errors."