Exam 1 Flashcards
strategic decisions
- involve higher level issues concerned with the overall direction of the organization
- define the organization’s overall goals and aspirations for the future
tactical decisions
- concern how the organization should achieve the goals and objectives set by its strategy
- are usually the responsibility of midlevel management
operational decisions
- affect how the firm is run from day to day
- are the domain of first line managers who are closest to the customer
common approaches to decision making
- tradition
- intuition
- rules of thumb
- sacred cow
- using the relevant data available
business analytics
- scientific process of transforming data into insight for making better decisions
- used for data-driven or fact-based decision making, which is often seen as more objective than other alternatives for decision making
descriptive analytics
-the use of data to understand past and current business performance and make informed decisions
predictive analytics
-predict the future by examining historical data, detecting patterns or relationships in these data, and then extrapolating these relationships forward in time
prescriptive analytics
-identify the best alternatives to minimize or maximize some objective
optimization models
- part of prescriptive analytics
- models that give the best decision subject to constraints of the situation
decision analytics
- part of prescriptive analytics
- used to develop an optimal strategy when a decision maker is faced with several decision alternatives and an uncertain set of future events
big data
-any set of data that is too large or too complex to be handled by standard data-processing techniques and typical desktop software
cross-sectional data
data collected from several entities at the same, or approximately the same, point in time
time series data
data collected over several time periods
frequency distribution
a summary of data that shows the number (frequency) of observations in each of several non-overlapping classes (bins)
histogram
a common graphical presentation of quantitative data
arithmetic mean
average of a set of numerical values
skewness
an important numerical measure of the shape of a distribution
range
subtracting smallest value from the largest value
variance
- a measure of variability that utilizes all the data
- based on the deviation of the observations from the mean
standard deviation
-the positive square root of the variance
coefficient of variation
descriptive statistic that indicates how large the standard deviation is relative to the mean
data visualization
- first step in interpreting data
- creating a summary table for data
- generating charts to represent data
data ink ratio
- remove unnecessary non-data ink
- de-emphasize and regularize the remaining non-data ink
- emphasize the most important data ink
when to use tables
- to look up and compare individual values
- data must be precise
when to use graphs
- to see patterns, trends, relationships, and exceptions, to make broader comparisons
- to rapidly get a sense of the story
percentile
the value of a variable at which a specified (approximate) percentage of observations are below that value
quartile
division points when data is divided into four equal parts
IQR
interquartile range
-difference between third and first quartiles
z-score
measures the relative location of a value in the data set
- helps to determine how far a particular value is from the mean relative to the data set’s standard deviation
- often called the standardized value
outliers
extreme values in a data set
- may be incorrectly recorded
- may be from an observation that doesn’t belong to the population we are studying
box plot
- a graphical summary of the distribution of data
- developed from the quartiles for a data set
scatter chart
- useful graph for analyzing the relationship between two variables
- also suggests a trend line could be used as an approximation for the relationship between variables
covariance
a descriptive measure of the linear association between two variables
correlation coefficient
-measures the linear relationship between two variables
parallel coordinates plot
- used for plotting multivariate, numerical data
- ideal for comparing many variables together and seeing the relationships between them
regression analysis
-a statistical tool that examines the relationship between two or more variables so that one may be predicted from the other(s)
simple linear regression model
-the equation that describes how y is related to x and an error term
experimental region
the range of values of the independent variables in the data used to estimate the simple linear regression model
extrapolation
prediction of the value of the dependent variable outside the experimental region
multiple regression model
the equation that describes how the dependent variable y is related to the independent variables x1,x2,x3…, and an error term
multicollinearity
-the correlation among the independent variables in multiple regression analysis
time series
a sequence of observations on a variable measured at successive points in time or over successive periods of time
-objective of analysis is to uncover a pattern in the time series and then extrapolate the pattern into the future
horizontal time series pattern
exists when the data fluctuate randomly around a constant mean overtime
trend pattern
shows gradual shifts or movements to relatively higher or lower values over a longer period of time
-usually a result of long-term factors
seasonal pattern
-recurring patterns over successive periods of time
cyclical pattern
exists if the time series plot shows an alternating sequence of points below and above the trend line that lasts for multiple years
forecast error
difference between the actual and the forecasted values for period t
MFE
mean forecast error
-mean or average of the errors
MAE
mean absolute error
-measure of forecast accuracy that avoids problem of positive and negative errors offsetting one another
MSE
measure that avoids the problem of positive and negative errors offsetting each other
-computing the average of the squared forecast errors
MAPE
- mean absolute percentage error
- average of the absolute value of percentage forecast errors
moving averages
-use the average of the most recent k data values in the time series as the forecast for the next period
exponential smoothing
uses a weighted average of past time series values as a forecast
Four v’s of big data
Volume
Velocity
Veracity
Variety
Veracity
How much uncertainty is in the data
