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Classify the Survey Questions: Select all that apply What is your favorite color? Categorical Data Quantitative Data Univariate Data Bivariate Data Classify the Survey Questions:

Classify the Survey Questions: Select all that apply

What is your favorite color?

Categorical Data

Quantitative Data

Univariate Data

Bivariate Data

Classify the Survey Questions: Select all that apply

What type of ice cream do you prefer and what is your favorite topping to put on top?

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Quantitative Data

Univariate Data

Bivariate Data

Classify the Survey Questions: Select all that apply

How many cups of coffee do you drink in a week?

Categorical Data

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Univariate Data

Bivariate Data

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\fQUESTION B Select the techniques data scientist use when feature engineering Binning One-hot encoding Log transformation Outlier detection Multivariate analysis Exploratory data analysis QUESTION 9 What are the three types of descriptive methods data scientists use to explore data? Logistic regression Univariate analysis T-tests Bivariate analysis Multivariate analysis ANOVA QUESTION 10 When exploring the center, shape and spread of the data, data scientists analyze the data by exploring these measures: Mean, Median, Mode Interquartile range O Frequencies Multiple regressionThe following equation is estimated, where you is also an explanatory variable and the following results are obtained: y, = 2.7 +0.4x, + 0.9y,-1 (0.4) (0.06) n=200, R? =0.98, and DW=1.9 a. What does the Durbin Watson statistic test? What assumptions are used to calculate the Durbin- Watson statistic? For a DW of 1.9, what does this imply about the regression equation? b. Irrespective of your answer in part (a), how would you correct for AR(1) in this model?Which of the following are true of binary classication/ regression trees? i. Bagging decision trees is likely to increase the model variance. ii. The deeper the decision tree is, the more likely it is to overt. iii. They are robust to small changes in the data. iv. Random forests are less likely to overt than decision trees

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