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SAS Statistics Practice Exam > SAS Statistics Practice Exam > Flashcards

SAS Statistics Practice Exam Flashcards

Practice for certification

1
Q

What is the order of steps in both traditional statistical analyses and machine learning approaches to modeling?

A

Data exploration, variable modification, model fitting, model assessment

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2
Q

Which task is best suited for deep learning as opposed to other machine learning techniques?

A

Recognizing the objects in an image or video.

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3
Q

Which basic principle of statistics reflects the strength of support for results that are subject to small perturbations in input data?

A

Stability

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4
Q

You are gathering data on purchase size of fountain drinks ranging from small to extra-large. What is the level of measurement for size?

A

Ordinal

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5
Q

Which term has a different meaning than the other three?

A

Field

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6
Q

Which terms refer to the same component of an analytical data set? (Choose 2.)

A

Object, Entity

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7
Q

Which is an example of probability sampling?

A

Players are selected for teams by flipping a coin.

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8
Q

Which type of sampling is used when the population is divided into groups using a categorical variable and then observations are randomly selected from these groups?

A

Stratified Sampling

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9
Q

When you draw a sample of 10 balls from a bag of 100 balls of two colors using simple random sampling, what is the probability of each ball being selected?

A

1/100

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10
Q

Differences in values can be meaningfully calculated for variables on which scales?

A

Ratio and Interval

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11
Q

Which describes p-values in hypothesis testing?

A

A smaller p-value indicates stronger evidence against the null hypothesis.

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12
Q

A lighting company claims that their LED light bulbs surpass the typical lifespan of traditional incandescent bulbs, which is 1000 hours. After examining a sample of 50 LED bulbs, the sample mean is 2200 hours, and the sample standard deviation is 200 hours. What statistical test is appropriate for determining if the new LED bulbs, on average, outlast traditional incandescent bulbs?

A

One-sample t-test

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13
Q

Which measure quantifies the variability of an estimate, such as the sample mean?

A

Standard errror

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14
Q

Which describes a Type II error?

A

Failing to reject the null hypothesis that is false.

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15
Q

For an analysis in which the null hypothesis is known to be true, you perform a hypothesis test with α = 0.05. The analysis returns a p-value of 0.023. What does this demonstrate?

A

Type I error

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16
Q

For an analysis in which the null hypothesis is known to be false, you perform a hypothesis test with α = 0.05. The analysis returns a p-value of 0.23. What does this demonstrate?

A

Type II error

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17
Q

You measure patient blood pressure before and after each patient is administered a drug. How do you test the hypothesis that blood pressure remains the same before and after the drug is administered?

A

Paired t-test

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18
Q

What is Pearson’s correlation coefficient (r) used for?

A

Detect collinearity

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19
Q

Which of the relationships shown in the scatter plots below can be appropriately interpreted using a Pearson correlation coefficient? (Choose 2.)

A

Pearson correlation coefficients measure the strength of linear relationship, including no relationship. The Pearson correlation coefficient is not appropriate for non-linear relationships such as quadratic and cyclical.

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20
Q

In a simple linear regression model where x predicts y, R2 = 0.6. What can you conclude from this information?

A

60% of the variance in y is explained by x.

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21
Q

The Pearson’s correlation coefficient between x and y is 0.6. What can you conclude from this information?

A

The estimated linear association between x and y is 0.6.

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22
Q

In a simple linear regression model where x predicts y, estimated β0 = 0.6. What can you conclude from this information?

A

When x=0, the predicted value of y is 0.6.

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23
Q

In a simple linear regression model where x predicts y, estimated β1 = 0.6. What can you conclude from this information?

A

A one-unit change in x results in a predicted change in y of 0.6.

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24
Q

Which displays a Pearson’s correlation coefficient of 0.7?

A

This graph shows a moderately strong positive linear association. /

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25
Q

Which two values are divided to get the R-Square of 0.3751?

A

6593.01614, 17579

26
Q

Which describe information criteria statistics? (Choose 2.)

A

A model with a lower value shows better fit than a model with a higher value., They allow comparison between models fitted to the same data.

27
Q

Which of the following information criteria, due to its larger penalty, favors models with fewer parameters?

A

SBC

28
Q

How many parameters are estimated when fitting a linear regression model with 3 continuous predictors and one categorical predictor with 3 levels?

A

6

29
Q

Comparing two multiple linear regression models, which statistic indicates better model fit with larger values?

A

Adjusted R-square

30
Q

Performing a multiple linear regression analysis, which variable will be removed in backward elimination?

A

x5

31
Q

Which phases of predictive modeling require a known target?

A

Training a model but not scoring a new data.

32
Q

Which avoids an overly optimistic assessment of a predictive model’s performance?

A

Assess the model performance on a data set not involved in fitting the model.

33
Q

In terms of accuracy and precision, which indicates overfitting in a predictive model?

A

High accuracy and low precision

34
Q

Which activities use a model to generate predictions for a data set that does not contain a target variable? (Choose 2.)

A

Model deployment, Model scoring

35
Q

Which describes explanatory modeling?

A

It is used to test an already existing set of hypotheses.

36
Q

An odds ratio of Group A to Group B is 4, with a 95% confidence interval [3,5]. What can be inferred from this?

A

Group B has 0.25 times the odds of the target event as Group A.

37
Q

To test an association between two categorical variables for statistical significance, we use which statistic?

A

Chi-square statistic

38
Q

What can a chi-square test be used for? (Choose 2.)

A

Feature selection in machine learning., Test the statistical significance of association between two categorical variables.

39
Q

In logistic regression model assessment, which indicates the best fit?

A

Maximize concordant pairs; Minimize discordant and tied pairs

40
Q

What characterizes a discordant pair? (Choose 2.)

A

Model cannot sort the event and non-event pair correctly., An observation with the event has a lower predicted probability of having the event than an observation without the event.

41
Q

Using a cutoff of 35%, which Customer IDs would be classified as non-purchasers? (Choose 2.)

A

2, 4

42
Q

A logistic regression is fit using maximum likelihood parameter estimation. How many times is the model refit when used to score new data sets?

A

Zero

43
Q

What is the default cut-off for classification allocation, in logistic regression?

A

0.5

44
Q

You are using a cutoff probability for logistic discrimination, where cases above the cutoff are allocated to class 1 (event) and cases below the cutoff are allocated to class 0 (non-event). What best describes this allocation rule?

A

The decision boundary is linear irrespective of the cutoff.

45
Q

You are using a logistic regression model to score an observation. The predicted logit for the observation is zero (0). What is the predicted probability for this observation?

A

0.5

46
Q

Which type of machine learning algorithm would you use if some of the training data has labels but most of it doesn’t?

A

Semi-Supervised Learning

47
Q

A neural network with no hidden layer, one interval target, and a linear function of inputs resembles which of the following statistical models?

A

Linear regression

48
Q

What type of learning are nearest-neighbor mapping, k-means clustering, and singular value decomposition?

A

Unsupervised

49
Q

Which machine learning method is used when the cost associated with labeling is too high to allow for a full set of labeled training cases, but partial labeling information is available?

A

Semi-Supervised Learning

50
Q

A retail company wants to segment their customers into distinct groups based only on their demographic inputs. Which machine learning method is recommended?

A

Unsupervised learning

51
Q

A researcher is conducting a study on the effects of a new medication on blood pressure over a 12-week period. Due to scheduling conflicts, 25 out of 300 participants missed their week 6 check-up. The researcher believes that the likelihood of missing the check-up is related to the participants’ work schedules and not their actual blood pressure levels.

A

Missing at Random (MAR)

52
Q

Which machine learning algorithm is less sensitive to unevenly scaled data, and may not necessarily require you to scale a set of features in your data?

A

Decision Tree

53
Q

Which missing data mechanism in a regression analysis would result in the slope being biased and the R-square value being reduced?

A

Missing Not at Random (MNAR)

54
Q

You are analyzing data for a predictive model, in which the target is whether a customer is likely to purchase a product. Some of the values of the variable Customer Spend are missing. You find out that this is due to random fluctuations in server traffic, occasionally observations in the database are corrupted, resulting in a small amount of missingness.

A

Missing completely at random (MCAR)

55
Q

You are analyzing data for a predictive model, in which the target is whether a customer is likely to purchase a product. Some of the values of the variable Customer Spend are missing. You find out that this is because spending data is only collected for customers who have purchased the product.

What is the most likely data missingness pattern?

A

Missing not at random (MNAR)

56
Q

You are analyzing data for a predictive model, in which the target is whether a customer is likely to purchase a product. Some of the values of the variable Customer Spend are missing. You find out that this is due to a power outage that caused some of the data values to be corrupted from a specific region, resulting in a small amount of missingness in your training data.

A

Missing at random (MAR)

57
Q

Which are the most interpretable models? (Choose 2.)

A

Regression, Decision Tree

58
Q

The observed frequency for Bonus Eligible and Irregular Lot Shape is 31. What is the expected frequency for this cell?

A

13.6856
(Row TotalColumn Total) / Sample Size = (9344) / 299 = 13.6856

59
Q

In an online sale, 2500 OrderID’s were generated on a given day, out of which 125 values of OrderID variable were unique. What is the cardinality of OrderID variable?

A

125

60
Q

If an observation with the target event has the same predicted probability as another observation without the target event, what type of pair is this?

A

Tie

SAS Statistics Practice Exam (1 decks)

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