Identify and discuss the several aspects of univariate analysis.
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Identify and discuss the several aspects
of univariate analysis.
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- Explain whether each scenario below is a regression, classification, or unsupervised learn- ing problem. If it is a supervised learning scenario, indicate whether we are more interested in inference or prediction. Finally, provide in each case the number of observations, n, and the number of predictors, p. (1) An online retailer must decide whether to display advertisement A or advertisement B to each customer on the basis of collected customer demographics (age, income, zip code, and gender). A set of 150 of its customers have already expressed a preference for one advertisement or the other. (2) A policy analyst is interested in discovering factors that are associated with the crime rate across different U.S. cities. For each of 500 cities, the policy analyst gathers the following data: the crime rate, unemployment rate, population, median income, median home price, and state. (3) The the channel owner to see where the subscribers are located, their age and gender, the times and days…Suppose a doctor measures the height, x, and head circumference, y, of 11 children and obtains the data below. The correlation coefficient is 0.904 and the least squares regression line is y=0.208x+11.736. Complete parts (a) and (b) below.Is Data analysis methods: description of the data analysis methods is clear and appropriate? Thematic analysis was utilized in which themes from the data of the interviews, questionnaire, and phone call were identified by grouping similar answers into larger categories. Major themes emerged in the process of grouping. These themes were then organized into minor themes. Open coding, or initial coding was utilized for the data where fragments of data such as keywords, incidents, etc. were studied closely for analytic import. "Initial coding continues the interaction that you shared with your participants while collecting data but brings you into an interactive analytic space (Silipigni Connaway, L., &, Radford, M. L., 2021). The software that seemed best for the study that was used was MicroCase, a statistical analysis and data management system, as it developed with social science researchers in mind to utilize, and the area of workplace ageism as derived from social interaction…
- 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 C1 START NUM>> 1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 43 45 47 C1 START NUM>> 49 51 53 55 57 59 73 C2 RUN 38.23 37.10 40.07 38.28 40.83 43.62 38,27 41.75 38.77 37.13 37.12 45.32 42.77 43.58 32.97 33.23 32.57 32.18 32.00 34.60 33.65 33.32 34.52 33.30 37.18 36.55 34.42 37.78 36.53 32.95 36.70 35.13 31.42 36.37 36.38 36.92 33.37 37.18 35.25 Udle C2 RUN 36.40 35.52 35.15 31.35 36.03 34.43 36.22 TH+ +++ C3 T1 0.68 0.73 0.75 0.85 0.90 1.15 0.83 1.02 0.83 0.72 0.58 0.78 0.55 0.82 0.52 0.65 0.67 0.57 0.62 0.73 0.80 0.60 0.83 0.70 1.00 0.83 0.88 0.68 0.65 0.75 0.95 0.82 0.78 0.82 0.82 0.65 0.72 0.83 0.75 C3 T1 0.75 0.60 0.73 0.65 0.72 1.02 0.78 C4 CYCLE 34.52 35.60 37.53 34.72 36.63 38.70 34.75 36.52 34.25 36.40 35.33 42.58 40.28 35.90 26.87 28.65 27.10 27.87 28.68 27.77 30.78 28.60 28.15 29.62 28.38 33.55…Seven North American Green Frogs (Rana clamitans) had their jumping distance recorded (in mm) multiple times in a laboratory. The mean jumping distance for these frogs along with their length (measured from snout to vent in miMillimeters) are presented in the table below. Length of Frog 52 68 37 65 77 81 59 Mean Jumping Distance 546 673 415 659 793 814 563 (a) Determine the linear regression model that will best predit the mean jumping distance of a North American Green Frog based on the frog's length. (b) How well does the linear regression model fit this sample data? (c) Use the linear regression model to predict the mean jumping distance of a North American Green Frog that is 48 mm in length. No excel, please.An experiment was run and the following data table was produced: (a) Calculate the correlation coefficient for the data. Is the data positivelyor negatively correlated, and is that correlation weak, moderate, or strong?(b) Find the equation of the least squares regression line and plot the lineon top of a scatterplot of the data.
- The results obtained above were primarily due to the mean for the third treatment being noticeably different from the other two sample means. For the following data, the scores are the same as above except that the difference between treatments was reduced by moving the third treatment closer to the other two samples. In particular, 3 points have been subtracted from each score in the third sample. Before you begin the calculation, predict how the changes in the data should influence the outcome of the analysis. That is, how will the F-ratio for these data compare with the F-ratio from above? Treatment A Treatment B Treatment C 1 4 3 2 1 1 3 2 7 2 3 4 F-ratio = p-value = Conclusion: O These data do not provide evidence of a difference between the treatments O There is a significant difference between treatmentsState the large-sample distribution of the instrumental variables estimator for the simple linear regression model, and how it can be used for the construction of interval estimates and hypothesis tests.What does the correlation matrix for a multiple regression analysis contain?A. Multiple correlation coefficientsB. Simple correlation coefficientsC. Multiple coefficients of determinationD. Multiple standard errors of estimate
- Look at the Table, specifically the information related to "stroke severity." What is the dependent and the independent variables? Provide an interpretation of the coefficient (coeff), standard error (SE), and p-value for temperature & previous stroke.You are analyzing a dataset containing 379 datapoints, and want to use 13 predictor variables to create a multiple variable linear regression model of the data. You conduct an ANOVA analysis, and yield a R² of 38%. Using this information, what would be the F statistic of your analysis?4) In a univariate linear regression, explain intuitively, graphically and mathematically, how the variance of the estimated slope depends on a) the number of observations; b) the mean squared deviation of the independent variable; c) What else does it depend on? Can you explain how?
