BSAN 160 EXAM REVIEW QUESTIONS AND ANSWERS RATED 100% CORRECT!!!

T or F:Decision support system are computer-based support systems that integrate individuals' expertise and computer capabilities, and they have precise definitions agreed to by practitioners. - ANS-False Business Intelligence (BI) - ANS-is an umbrella term that combines architectures, databases, analytical tools, applications, and methodologies T or F: Data is a collection of observations, experiments, and experiences that do not necessarily represent absolute facts that are universally true. - ANS-True Descriptive Analytics - ANS-help managers understand current events in the organization including causes, trends, and patterns. What type of analytics seeks to recognize what is going on as well as the likely forecast and make decisions to achieve the best performance possible? - ANS-Prescriptive Which of the following is/are predictive analytics method(s)? A)Boxplot B)Text analysis C)Simulation D)Regression analysis, E)Clustering B, D and EB, C and ED and E - ANS-B, D, E Using characteristics of first year undergraduate students, such as age, gender, major, location, workout/sports activities, if we developed a model to forecast which students are at risk of dropping out after the first year of college, decided which students to reach out to and offered them support services to reduce their risk of dropping out, what kind of analytics application would this work represent? - ANS-prescriptive analytics Which chart type below would be most helpful to show the comparison between worldwide turnover rate compared with tech sector turnover rate? Line chart Histogram Bar chart Scatterplot - ANS-Bar chart Which chart type below would be most helpful to show the relative proportions of turnover rate of different categories (e.g., computer games, Internet, computer software and other) within the tech sector that drive tech turnover the most? Histogram Pie chart Bar chart Scatterplot - ANS-Pie Chart T or F: Original (raw) data is usually collected from multiple data sources including various formats, and it is readily usable by analytics tools and algorithms - ANS-False T or F: During data transformation, depending on the context and purpose of preprocessing the data can be rescaled to a fixed range, and numeric variables can be converted to categorical variables - ANS-True T or F: Data reduction can be applied to rows (observations) and/or columns (variables) in a given dataset - ANS-True T or F: In data preprocessing step to reduce the dimension of data prior to analysis, sampling the rows is more complex than selecting the columns (variables - ANS-False T or F: Choice of visualization method that meets the presentation requirements for a given data depends on the data types available, purpose of the visual and context - ANS-True Which of the below is not a data preprocessing step? data consolidation data transformation data separation data reduction - ANS-data seperation Which of the below is a method to deal with filling out the missing values in data? data cleaning data reduction data smoothing data imputation - ANS-data imputations Which of the below statement(s) is/are correct? A: An important data transformation subtask is to select the relevant data using domain expert input, i.e., decide which sources and data to collect. B: When merging two data source tables A and B, using the full outer join method eliminates all rows from the resulting table that do not have corresponding rows in both source tables A and B. C: For numerical variables, normalizing the observed values between two values, such as 0 and 1, allows to rescale the values and compare variables with different means and/or standard deviations on a single scale. D: Identifying and reducing noise in the data is a subtask of data reduction. - ANS-C When analyzing the original data of household income of a selected population, analysts notice that 5% of observations are missing and entered in the dataset as N/A (not available). Further, they notice that there are a few extremely low household income values. Which of the following method(s) would be well-suited to prepare the data before conducting descriptive analysis, such as calculating descriptive statistics and creating histogram of household income? A: Use the original dataset to avoid introducing additional noise to data prior to analysis B: Identify the outliers in data with statistical techniques and remove the extremely low income values C: Identify the outliers in data with statistical techniques and replace the extremely low values using the mean of the income values to smooth the values D: Fill in missing values (imputations) with most appropriate values using zeros to indicate that these income valu - ANS-B and C Which of the below statement(s) is/are correct? A: Information dashboards provide interactive visual displays of important information that is so that the level of granularity of key insights can modified by drilled in or moving out for more / less exploration B: Visual analytics combines data visualization and different analytics methods such as descriptive, predictive and prescriptive analytics. C: Interactive information dashboards provide key insights as static information that focus on better understanding of what happened. - ANS-A and B Which of the following data preprocessing activity/activities that Mia conducts would fall under data transformation? A: Identify and replace extremely high and low selling price values using appropriate imputation methods B: Convert number of bikes sold per month (numeric) into discrete categories using frequency-based bins C: Filter the data to ensure that only key performance and price features needed for the analysis are included in the data D: Reduce the range of values of quarterly market share (numeric) data to a standard range (e.g., 0 to 1 or -1 to +1) by using normalization or scaling techniques E: Oversample the less represented financial performance measurements - ANS-B and D Which chart should Mia use to visualize the relative proportion of market share of Peloton in 2020 compared to its competitors Nordic Track, Myx Fitness, and Echelon? - ANS-Pie chart Which chart should Mia use to visualize the number of new members joining the Peloton customer community every month from 2012 to 2020? - ANS-Line chart Which of the following data preprocessing activity that Mia conducts is not associated with data cleaning? - ANS-Derive a new variable representing total time of class material from existing variables Mia decides to use imputation methods as part of the data preprocessing. What is the main purpose of imputation methods? - ANS-Fill in missing values with most appropriate values T or F Linear regression models represent the mathematical relationship between one or more dependent variables to explain or predict a binary (i.e., a variable that takes values 0=no and 1=yes) independent variable." - ANS-False T or F: "Linear regression analysis can be used to predict an unknown value of a dependent variable using the values of a set of numeric and/or categorical independent variables." - ANS-True Comparing two regression models (Model 1 and Model 2) developed using the same dataset, assume Model 1 has an R-squared of 0.58 and Model 2 has an R-squared of 0.79. Which of the following statement(s) is/are correct? A: Model 2 describes 79% of the variation in the given data B: Comparing both models and how well they explain the variation in the given data, Model 1 is a better fit compared to Model 2 C: The independent variables used in Model 1 do not capture 42% of the variation in the given data - ANS-A and C T or F: "Using the correlation between size and selling price, we can predict the selling price of a new house (that is not included in this dataset) if we know the size of that new house." - ANS-False T or F: "If the correlation between size and selling price of a house is 0.85, and we develop a simple regression model using size as independent and selling price as the dependent variable, the slope coefficient associated with size in the regression equation would have a positive sign." - ANS-True Assume we develop a regression model to predict the final grade of a student using the following variables: midterm grade, time spent studying for the final exam, number of other classes the student is taking the same term, whether the student took a similar class before (yes or no) and whether the student is female (1=female or 0=male). Which of the following statement(s) is/are correct? - ANS-This model is a multiple linear regression model Using Figure 1, test the hypothesis that students with higher high school GPA percentile have a higher SAT score compared to students with a lower high school GPA percentile. In other words, we want to test if we increase the high school GPA percentile of a student by 1% then their SAT score will also increase. Which of the following method would help to test this hypothesis? - ANS-Simple linear regression with high school percentile as the independent and SAT as the dependent variable Assume we fit a regression line to the scatterplot in Figure 1 from Question 1. Which of the following statement(s) is/are correct? A: The intercept of the line would represent the high school GPA percentile of a student given his/her/their SAT score is 0. B: The intercept of the line would represent the SAT score of a student given his/her/their high school GPA percentile is 0. C: The slope of the regression line would represent how much the SAT score changes if the high school GPA percentile changes by 1% D: The slope of the regression line will be positive - ANS-B C and D Using the dataset of 178 students from Question 1, your team develops a regression model to predict the Combined score of a student (i.e., score that the school uses to rank applicants) using HSPercentile (i.e., high school GPA percentile and it takes values from 0 to 1 where 1 represents the 100th percentile meaning maximum), Gender (where Female=0 and Male=1) and the student's SAT score. The regression equation is given by: CombinedScore =118.95 + 1.91*HSPercentile -1.74*(Gender) + 0.06*SAT This model is a ______________ regression model. - ANS-Multiple Linear Assume there are two students, Neal and Jimmy, with the same high school GPA percentile and gender, and Neal's SAT score is one point higher than Jimmy's. Using the regression model shown in Question 3, Neal's predicted combined score would be _______. - ANS-0.06 higher than Jimmy's combined score A regression model is developed to predict which students will be retained in second year (i.e., still enrolled in second year). Using various characteristics of the 178 students in the given dataset, the variable we want to predict is "SecondFallRegistered" which is either yes (=1) if the student is still enrolled in second year (measure of retention), or no (=0) if student dropped out between the beginning of first year and second year of college. In this case, a ______________ regression model would be the best suited model to predict the variable SecondFallRegistered. - ANS-Logistic Given the model predicted that a student would be retained, __________ is a measure that quantifies the ratio of number of students who actually were retained compared to all students that were predicted to be retained. The value of this measure is this example is ___________. - ANS-Precision, 2/46 Given a student was retained, the number of times the model predicted a student's retention correctly is called ____________. The value of this measure is this example is ___________. - ANS-Recall, 2/23 T or F: "The relational data in a data warehouse are modified and analyzed using Online Analytical Processing (OLAP) tools. Commonly used OLAP tools are slice, dice, drill up and down, and pivot." - ANS-True When querying a dimensional database, a user goes from summarized data (e.g., quarters) to its underlying details (e.g, months). The OLAP function that serves this purpose is: - ANS-Drill Down When querying a dimensional database, a user transforms the data coming from rows of a table into data grouped on several columns. The OLAP function that serves this purpose is: - A