Data Analytics Exam 3

The key distinction between supervised and unsupervised data mining is that the identification of the target variable is identified in supervised data mining.

True

The process of applying a set of analytical techniques for the development of machine learning and artificial intelligence is called data mining.

True

Using the 95% prediction interval data below, what is the mean net profit/loss range when x1 = $5 million and x2 = $3.5 million and the standard error is 0.2144? (pic 4)

$190,000 to $1,050,000

If there is a 30,000 average Service Cost in marketing services, with a 70% Cost Increase and 60% of client Payment for services upfront in addition to advantages of City, the predicted annual earnings for the firm are: (pic 2)

$46,534.38.

Using the 95% confidence interval data below, what is the mean net profit/loss range when x1 = $5 million and x2 = $3.5 million and the standard error is 0.2144? (pic 3)

$570,000 to $680,000

In a study where the least squares estimates were based on 34 sets of sample observations, the total sum of squares and regression sum of squares were found to be: SST = 4.53 and SSR = 4.21. What is the error sum of squares?

0.32

If SSE = 200 and SSR = 300, then the coefficient of determination is

0.60.

If SST = 2,500 and SSE = 575, then the coefficient of determination is

0.77.

In a simple linear regression based on 20 observations, it is found b1 = 3.25 and se(b1) = 1.35. Consider the hypothesis: H0 : β1 ≠ 0 and HA : β1 ≠ 0 . Calculate the value of the test statistic.

2.41

How many dummy variables will be created if the following four modes of transportation to work are captured: biking, public transportation, driving alone, and carpooling?

3

In the goodness-of-fit measures, interpret the coefficient of determination for Earnings with Model 3 and what the sample variation of Earnings explains. (pic 6)

42.88% of the sample variation in Earnings is explained by the regression model.

Based on goodness-of-fit measures, what is the percentage of the sample variation unexplained by Model 2? (pic 7)

59.77%

If the coefficient of the determination is 0.60, what is the percent of the R2?

60%

If R2 = 0.62, then how much of the sample variation is y?

62%

In the following equation ŷ = 30,000 + 4x with given sales (γ in $500) and marketing (x in dollars), what does the equation imply?

An increase of $1 in marketing is associated with an increase of $2,000 in sales.

Cross-Industry Standard Process for Data Mining (CRISP-DM) consists of six phases. Which of the following is the first phase?

Business understanding

Cross-Industry Standard Process for Data Mining (CRISP-DM) consists of six phases. Of the six, which one represents the phase where data wrangling occurs?

Data preparation

Based on the following table, what is the sample regression equation? (pic 1)

Earnings = 10,004.9665 + 0.4349Cost + 178.0989Grad + 141.4783Debt

Common applications of unsupervised learning include dimension reduction and prediction model.

False

In a linear regression model, the competing hypotheses take all but which form?

H0:βj > βj0 and HA:βj ≠ βj0

In Excel, to construct a residual plot, input of a y range and an x range is needed. Aimee is examining the relationship between age and square foot range (sqft) of living space. In the scenario provided, what would be the y and what would be the x range data?

Input y range would be age and Input x range would be sqft.

Which of the following statements about Adjusted R2 is false?

It is possible to increase Adjusted R2 unintentionally by including a predictor variable that has no foundation in the model.

The slope coefficient β, is called

beta.

It is important to review residual plots to identify any signs of _____________blank and correlated observations in cross-sectional and time-series studies.

changing variability

If ŷ = 110 − 5x with y = product and x = price of product, what happens to the demand if the price is increased by 3 units?

decreases by 15 units

Which one of the following is not a common violation in the test of validity?

estimation

The simple linear regression model y = β0 + β1x + ɛ implies that if x _____________blank, we expect y to change by β1, irrespective of the value of x.

goes up by one unit

When determining if there is evidence of a linear relationship between variables, OLS estimators must be _____________blank for the test to be valid.

normally distributed

To conduct a test of joint significance, you want to employ which test?

right-tailed F test

Which of the following is not a goodness-of-fit measure?

simple regression model

The Department of Natural Resources conducted a study examining the condition of fish in the Wolfe River (Wisconsin). In total 110 fish were captured. The variables that were measured are: mile marker of location in river, species (rainbow trout, northern pike, musky, walleye, and panfish), length, and weight. Which item is not numerical?

species

What is the relationship between the predictor variables and the response variable called when the omission of various relevant factors can influence the response variable?

stochastic

In a linear regression, ε, read as epsilon, is

the random error.

The standard error of the estimate is Se = SSE/(n − k − 1)−−−−−−−−−−−−−−−√SSE/(n - k - 1) . What result best fits the sample data?

when Se = 0.005

Abe is calculating a stock investment risk. If the hypothesis is H0 : β ≥ 1 HA : β < 1, the p-value 0.027, and α = 0.05, is the investment riskier than the market?

β is less than one, so the investment is less risky than the market.

Camber Seal is a financial planner hired to review KMB stock. She is considering the CAPM where the KMB risk-adjusted stock return R − Rf is used as the response variable and the risk-adjusted market return Rm − Rf is used as the predictor variable. KMB stock is considered staple products, whether the economy is good or bad. Given estimates for the beta coefficient is 0.7503, standard error of 0.1391, and a p-value of 0.039 with a formulated hypothesis of H0 : β ≥ 1 HA : β < 1. At a 5% significance level, what is the risk determination of the stock against the market?

β is significantly less than one, thus, H0 : is rejected and less risky than the market.

Conduct a test to determine if the predictor variables are jointly significant in explaining Earnings at α = 0.05. (pic 8)

P(F(1,18) ≥ 57.737), p-value is less than α = 0.05, we reject H0, and the predictor variables are jointly significant in explaining Earnings.

This represents which relationship?

Positive linear

The director of college admissions at a local university is trying to determine whether a student's high school GPA or SAT score is a better predictor of the student's subsequent college GPA. She formulates two models: Model 1. College GPA = β0 + β1High School GPA + ε Model 2. College GPA = β0 + β1SAT Score + ε She estimates these models and obtains the following goodness-of-fit measures. (pic 9)

Model 1 since it has a smaller standard error of the estimate and a higher coefficient of determination.

Based on goodness-of-fit measures, which is the preferred model based on the results below? (pic 5)

Model 3

Akiko Hamaguchi is a manager at a small sushi restaurant in Phoenix, Arizona. Akiko is concerned that the weak economic environment has hampered foot traffic in her area, thus causing a dramatic decline in sales. In order to offset the decline in sales, she has pursued a strong advertising campaign. She believes advertising expenditures have a positive influence on sales. To support her claim, Akiko estimates the following linear regression model: Sales = β0 + β1Unemployment + β2Advertising + ε. A portion of the regression results is shown in the accompanying table. (pic 11) a-1. Choose the appropriate hypotheses to test whether the predictor variables jointly influence sales. a-2. Find the value of the appropriate test statistic. a-3. At the 5% significance level, do the predictor variables jointly influence sales? b-1. Choose the hypotheses to test whether the unemployment rate is negatively related with sales. b-2. Find the p-value. b-3. At the 1% significance level, what is the conclusion to the test? c-1. Choose the appropriate hypotheses to test whether advertising expenditures are positively related with sales. c-2. Find the p-value. c-3. At the 1% significance level, what is the conclusion to the test?

a-1. H0: β1 = β2 = 0; HA: At least one βj ≠ 0 Correct a-2. 8.760 a-3. Yes since the F-test is significant. b-1. H0:β1≥0; versus HA:β1<0 b-2. 0.01 ≤ p-value < 0.025 b-3. Do not reject H0; we cannot conclude that the unemployment rate and sales are negatively related. c-1. H0:β2≤0; versus HA:β2>0 c-2. p-value < 0.01 c-3. Reject H0; advertising expenditures and sales are positively related.

In order to examine the relationship between the selling price of a used car and its age, an analyst uses data from 20 recent transactions and estimates Price = β0 + β1Age + ε. A portion of the regression results is shown in the accompanying table. (pic 10) a. Specify the competing hypotheses in order to determine whether the selling price of a used car and its age are linearly related. b. Calculate the value of the test statistic. c-1. Find the p-value. c-2. At the 5% significance level, is the age of a used car significant in explaining its selling price? d-1. Conduct a hypothesis test at the 5% significance level in order to determine if β1 differs from −1,000. d-2. Find the p-value. d-3. What is the conclusion to the test?

a. H0:β1=0; versus HA:β1≠0 b. -9.298 c-1. p-value < 0.01 c-2.. Yes we can conclude that the age of a used car is significant in explaining its selling price. d-1. -1.603 d-2. p-value 0.10 d-3. Do not reject H0, we cannot conclude that β1 ≠ -1,000