Exam 1: Lectures 1, 2, 3

Question 1

Business Analytics

Answer 1

refers to the skills, technologies, and practices for continuous iterative exploration and investigation of past business performance (e.g., sales and return on investment) to gain insight and drive business planning

Question 2

Descriptive Analytics

Answer 2

Tools that summarize what happened

Question 3

Prescriptive Analytics

Answer 3

Statistical techniques that make predictions and then suggest decision options to take advantage of the predictions

Question 4

Predictive Analytics

Answer 4

A variety of statistical techniques that analyze data to make predictions about future

Question 5

Business Analytics Advantages

Answer 5

1) Drive Revenue
2) Save Money
3) Encourage Experimentation
4) Side-step Politics
5) Persuade Executives

Question 6

4 Key Challenges in Doing Business Analytics

Answer 6

1) Managing 6V’s of Big Data
2) Growth of Unstructured Data
3) Underestimating the Hard Work
4) Hiring the Right Person(s)

Question 7

4 Main Elements of Data-Driven Tasks

Answer 7

1) Data Access
2) Data Management
3) Data analysis
4) Data presentation

Question 8

Model

Answer 8

an abstraction of a real problem that tries to capture the essence and key features of the problem

Question 9

Key Challenges of Managing 6V’s of Big Data

Answer 9

1) Volume
2) Velocity
3) Variety
4) Volatility
5) Validity
6) Value

Question 10

Volume

Answer 10

Big data implies large volumes of data

Question 11

Velocity

Answer 11

It is the speed of data processing

Question 12

Variety

Answer 12

Many sources and types of data are structured and unstructured

Question 13

Volatility

Answer 13

It refers to how long data is valid and how long it should be stored

Question 14

Validity

Answer 14

Data should be correct and accurate for the intended use

Question 15

Seven step modeling process

Answer 15

1) Define the problem
2) Collect and summarize data
3) Develop a model
4) Verify the model
5) Select one or more suitable decisions
6) Present the results to the organization
7) Implement the model and update it over time

Question 16

graphs

Answer 16

bar charts, pie charts, histograms, scatter charts, and time series graphs

Question 17

numerical summary measures

Answer 17

counts, percentages, averages, and measures of variability

Question 18

tables of summary measures

Answer 18

totals, averages, counts, and grouped by categories

Question 19

population

Answer 19

includes all of the entities of interest in a study (people, households, machines, etc.)

Question 20

sample

Answer 20

a subset of the population, often randomly chosen and preferably representative of the population as a whole

Question 21

Four Scales of Measurement

Answer 21

1) Nominal
2) Ordinal
3) Interval
4) Ratio

Question 22

Nominal

Answer 22

have two or more categories without having any kind of natural order, two levels: gender (male and female), multiple levels: marital status (single, married, divorced, widowed)

Question 23

ordinal

Answer 23

a categorical variable for which the possible categories are ordered, education level: less than high school, high school, college degree, graduate degree

Question 24

interval

Answer 24

measure is ordered and the distance between each number is equal; however, there is no natural zero condition, temperature: the difference between 10C and 20C is the same as the difference between 20C and 30C

Question 25

ratio

Answer 25

variables are interval variables, but with the added condition of zero (origin), money, sales revenue

Question 26

interquartile range

Answer 26

the third quartile minus the first quartile Thus, it is the range of the middle 50% of the data It is less sensitive to extreme values than the range

Question 27

variance

Answer 27

essentially the average of the squared deviations from the mean If Xi is a typical observation, its squared deviation from the mean is (Xi – mean)2

Question 28

range

Answer 28

the maximum value minus the minimum value

Question 29

standard deviation

Answer 29

the square root of the variance

Question 30

skewness

Answer 30

occurs when there is a lack of symmetry

Question 31

kurtosis

Answer 31

has to do with the “fatness” of the tails of the distribution relative to the tails of a normal distribution

Question 32

Statisticians generally consider a value as an outlier if

Answer 32

it is more than three standard deviations from the mean

Question 33

dummy variable

Answer 33

a 0–1 coded variable for a specific category It is coded as 1 for all observations in that category and 0 for all observations not in that category

Question 34

bin variable

Answer 34

corresponds to a numerical variable that has been categorized into discrete categories

Question 35

when a distribution has a negative (or positive) skew, ____ is larger than ____

Answer 35

median, mean

Question 36

Two Types of Estimators

Answer 36

1) Point Estimators 2) Interval Estimators

Question 37

Point Estimators

Answer 37

to estimate a population characteristic with a single value

Question 38

Interval Estimators

Answer 38

to estimate a population characteristic with an interval, or range, of values

Question 39

simple random sampling mechanism

Answer 39

the sample mean is typically used as a “best guess.” This estimate is a point estimate The accuracy of the point estimate is measured by its standard error It is the standard deviation of the sampling distribution of the point estimate A confidence interval (with 95% confidence) for the population mean extends to approximately two standard errors on either side of the sample mean From the central limit theorem, the sampling distributionof 𝑋 ̅ is approximately normal when n is reasonably large There is approximately a 95% chance that any particular 𝑋 ̅ will be within two standard errors of the population mean μ

Question 40

For a simple random sampling, if we have 10,000 customers and we want to select 1,000 customers at random; each customer should have ___ chance to be selected

Answer 40

1 in 10

Question 41

typical sampling mistakes

Answer 41

1) Unrepresentative sample 2) Biased respondents 3) Low response rate (non-response bias) 4) Biased questions

Question 42

unrepresentative sample

Answer 42

Sample does not represent population

Question 43

biased respondents

Answer 43

Respondents incorrectly answer sensitive questions such as annual income

Question 44

low response rate (non-response bias)

Answer 44

Only few respondents participate in surveys

Question 45

biased questions

Answer 45

Incorrect wordings make hard to understand what respondents answer

Question 46

confidence interval

Answer 46

a range of values we are fairly sure our true value lies in

Question 47

systematic sampling

Answer 47

is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point and a fixed periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size

Question 48

stratified sampling

Answer 48

Suppose various subpopulations within the total population can be identified. These subpopulations are strata Instead of taking a simple random sample from the entire population, it might make more sense to select a simple random sample from each stratum separately

Question 49

cluster sampling

Answer 49

the population is separated into clusters, such as cities or city blocks, and then a random sample of the clusters is selected

Question 50

p-value

Answer 50

the probability of obtaining a result equal to what was actually observed, when the null hypothesis is true

Question 51

What % of observations within 1, 2, or 3 standard deviations of its mean when a variable x follows a normal distribution

Answer 51

68, 95, 99.7

Question 52

When we reject or fail to reject null hypothesis at 0.05 significant level

Answer 52

p-value<0.05, rejected, p-value>0.05 fail to reject

Question 53

hypothesis

Answer 53

a claim that can be tested statistically

Question 54

one-tailed alternative

Answer 54

supported only by evidence in a single direction

Question 55

two-tailed alternative

Answer 55

supported by evidence in either of two directions

Question 56

how to deal with missing values in variables

Answer 56

One option is to simply ignore them. Then you will have to be aware of how the software deals with missing values Another option is to fill in missing values with the average of nonmissing values. We use this option! A third option is to examine the nonmissing values in the row of a missing value; these values might provide clues on what the missing value should be