Given observations (1,1), (2,1), (1,2), (5,5), (6,4), formulate a classification hypothesis and the corresponding decision boundary.
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- Answer it correctly please. I will rate accordingly with 4votes. I need correct answer and correct reason.With flu season upon us, each of us has important decisions to make if and when we fall ill. In the interest of discussing decision trees, let's assume that you've picked up an illness but you're not sure if it is just a cold virus, a more severe flu virus, or a penicillin treatable bacterial infection. There are two alternatives for you to consider:1.) Whether or not to see the doctor and have the doctor run the test to determine if the illness is a cold, flu, or bacterial.2.) Whether or not to treat the illness with penicillin (which will only be effective against a bacterial illness). The cost to go to the doctor and have the test is $200 and the cost of a penicillin prescription is $50. The chance of the illness being a cold is 50%, flu is 20%, and bacterial is 30%. The test results also match these ratios. If the test indicates that it is a cold, then there is a 80% likelihood that it is a cold. If the test indicates a flu virus, then there is a 90% likelihood that it is the flu.…A psychologist wants to test the influence of color on object recognition in 4-year olds. She recruits 25 children and shows them two sets of pictures of everyday objects (variable = picture type), has the children name them, and measures the time it takes (variable = reaction time). She shows the children a color set of pictures first and then shows them a black and white set of pictures. a) What is the independent variable? b) What is the dependent variable? c) What is the second independent variable? d) What is the second dependent variable? e) Is "picture type" a within-subjects or between-subjects variable? f) What scale of measurement is reaction time? g) What scale of measurement is picture type? h) The order of presentation of the picture sets is what kind of variable?
- 2. A researcher wants to determine which of three advertisements is most likely to encourage teens not to smoke. To assess the impact of each advertisement, she asks a sample of teenagers to view each ad and to rate the ad's effectiveness on a scale of 1 (not at all effective) to 7 (very effective). One ad used words only (no-cues condition), a second ad used a generic abstract picture (generic-cues condition), and a third showed a picture of a teen smoking and coughing (smoking-related cues condition). Fully test the question (5 steps) and determine the effect size. Participant ABCDEFG No Cues 2 3 1 4 4 5 2 T = 21 SS = 12 Generic Cues 5 5 4 5 3 4 2 T1 = 28 SS=8 Smoking- Related Cue 5 6 5 7 6 7 6 T2 = 42 SS = 4 P G = 91 ΣΧ2 = 4515. In recent years there has been a great deal of research demonstrating gender discrimination in science, technology, engineering and math (STEM) fields. In one experiment, for example, faculty members viewed an application for a laboratory manager position. The applications were identical except that half had a traditionally male name (John) and half had a traditionally female name (Jennifer). In addition, half of the faculty participants were from STEM fields and half were from non-STEM fields. The faculty were asked to rate the competence of the applicants on a 6-point scale, with 1 indicating a lower rating. Group means are presented below, along with an incomplete summary table. After completing the table, write a conclusion about the outcome of the experiment. Source Gender of applicant Male Female Between Treatments Gender of applicant Discipline of rater A x B interaction Within treatments Total SS 320 80 576 Discipline of Faculty Rater STEM M = 4.80 M = 4.02 df MS 20 1.25…The Alianz Arena is a football stadium in Munich home to Bayern Munich a German football club. The club have identified 12 potential camera locations within the stadium. They have also identified 25 stadium areas which may require camera coverage during the pre-game, game and post-game activities. The following table indicates each camera location and the stadium areas the camera can cover: Camera Location 1 2 3 4 5 6 7 8 9 10 11 12 Stadium Areas 1,3,4,6,7 8,4,7,12 2,5,9,11,13 1,2,18,19,21 3,6,10,12,14 8,14,15,16,17 18,21,24,25 2,10,16,23 1,6,11 20,22,24,25 2,4,6,8 1,6,12,17 Bayern Munich executives are concerned about the costs for the production. Consequently, they have set an objective of minimizing the number of camera locations. In seeking this objective they want at least one camera to be available to cover each stadium area. Camera location 9 is the "blimp," and executives have decided that the blimp will be used because of viewer expectation and fascination with the shots from…
- 8) The following results are from data that were collected from the various high schools around the county. The dependent variable is % OF STUDENTS GOING TO COLLEGE, and the independent variables are: AVERAGE CLASS SIZE, COMBINED SAT SCORES, SPENDING PER STUDENT, AVERAGE TEACHER SALARY, AND % TAKING THE SAT Since the 3 variables AVERAGE CLASS SIZE, SPENDING PER STUDENT, AND AVERAGE TEACHER SALARY are each not significant at the 10% level of significance individually, in order to test to see if as a group they are significant the 3 variables are excluded and another regression is run. The results are as follows: a) At the 10% level of significance, test whether as a group AVERAGE CLASS SIZE, SPENDING PER STUDENT, AND AVERAGE TEACHER SALARY are significant. Be sure to state the null and alternative hypotheses for this hypothesis test.Prof. Flores, always interested in improving her teaching effectiveness, has decided to undertake a careful analysis of her evaluations from the past three years. A matter of special concern to her is how she is viewed by students of different majors. She's decided to look at the last question on the teacher evaluation form, Question 17, which is, "Would you recommend this professor to another student?" Each of Prof. Flores' students can be placed into one of three categories according to the student's major school, as shown in the contingency table below. (Students who have majors from more than one school are not included.) This table contains a summary of the data that Prof. Flores has collected for 500 of her students. Each of the 500 students is classified according to two variables: major school ("School of Social Science", "School of Engineering", or "School of Physical Sciences") and response to Question 17 ("No", "Maybe", or "Yes"). In the cells of the table are written the…explain the different types of control group designs
- Westminster Financial has released a summary of investor and investment package information from the past fiscal year. During this time, Westminster provided a choice among 12 pre-designed investment packages. The investment packages were classified according to two variables: riskiness of investment package chosen ("Risky", "Moderate/mixed", and "Conservative") and age of investor ("Under 35", "35-49", or "50+"). Suppose that we're interested in the possible relationship between the age of the investor and the riskiness of the investment package the investor chose. The following contingency table gives a summary of the information released by Westminster regarding age and riskiness of investment package for 150 investors. In the cells of the table are the respective observed frequencies, and three of the cells also have blanks. Fill in these blanks with the frequencies expected if the two variables, riskiness of investment package chosen and age of investor, are independent. Round…In a survey of statistics students, it is found that 54 use RStudio, 43 use SAS, and 32 use Stata, for data analysis. Moreover, 29 use both RStudio and SAS, 18 use both RStudio and Stata, and 21 use both SAS and Stata, for data analysis. Fifteen of these students use RStudio, SAS, and Stata, while nine of them use tools other than R Studio, SAS, and Stata. a. How many students use RStudio only for data analysis? b. How many students use at least two software for data analysis? c. How many students use SAS or Stata, but not both?Delta Food Grocery has two grocery stores located in Bije City. One shop is located on Jalan Usman and the other on Jalan Sinda and each is run by a different manager. Every manager claims that his shop layout maximizes the number of impulsive customers. The two managers surveyed their sample of customers and asked them how much they were spending than they planned, in other words, how much they were spending on impulse (spending more than they planned). The following table shows sample data collected from the two shops. Jalan Usman (Rp 000) Jalan Sinda (Rp 000) 15.78 15.19 17.73 18.22 10.61 12.87 15.79 17.79 13.45 13.96 12.85 13.74 12.47 10.83 S1 = 2.5529 S2 = 2.5675 Top management at Delta Foods Grocery wanted to know if there was a difference in the mean amount of impulsive consumption between the two stores. Perform statistical analysis via: 1. Compile the null hypothesis and alternative hypothesis 2.…