Business Analytics- Quants

Who was incorrect in saying "my scientific studies have afforded me great gratification; and I am convinced that it will not be long before the whole world acknowledges the results of my work?"

Gregor Mendel

These have only two values, and for statistical analysis purposes it's often best to measure them as the presence or absence of something with values of 1 and 0. An example could be whether you are male or female (which could be recorded as 0 for no "femaleness," and 1 for being female), or whether you are a US citizen or not.

Binary Variables

Analysis of variance; a statistical test of whether the means of more than two groups are all equal.

ANOVA

If you want to see relationships among data points, use a

Scatterplot

There are at least six types of quantitative analytical stories. Which of the following is not one of those of types?

Analytical Story

the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact based management to drive decisions and add value

Analytics

If you want to compare a set of frequencies or values, typically for one variable, use a

Bar chart

These have several possible categories as values, such as eye color, flavors of ice cream, or which state or province you live in. Because they can't easily be converted into numbers where increases or decreases mean anything, there is a special class of statistics for categorical data.

Categorical (also called nominal) variables

The relationship between an event (the cause) and a second event (the effect), where the second event is understood as a consequence of the first. In common usage, causality is also the relationship between a set of factors (causes) and a phenomenon (the effect).

Causality

A statistical test that determines how well sample data fits a specified type of distribution.

Chi square (goodness-of-fit) test

is a main task of exploratory data mining, and a common technique for statistical data analysis used in many fields.

Clustering or Cluster analysis

The extent to which two or more variables are related to one another. The degree of relatedness is expressed as a correlation coefficient, which ranges from 1.0 to 1.0

Correlation

for example, perhaps the most widely used analytical software tool in the world (though most people think of it as a spreadsheet tool), can do some statistical analysis (and visual analytics) as well as reporting, but it's not the most robust statistical software if you have a lot of data or a complex statistical model to build.

Excel

tries to answer the questions of why something happened by conducting experiments.

Experimental design

The variable whose value is unknown that you would like to predict or explain.

Dependent variable

involve gathering, organizing, tabulating, and depicting data and then describing the characteristics about what is being studied.

Descriptive analytics

A statistical procedure that takes a large number of variables or objects and uncovers the underlying relationships among them.

Factor analysis

an effective method for reviewing previous findings.

Doing an Internet search for key terms related to your analysis

3 Stages of quantitative analysis

Framing the problem, Solving the problem, Communicating and acting on the results

The analytical thinking example, The Simon Hannes Insider Trading Case, is an example of how data analysis can be used to identify

Fraud

The most important thing in the problem recognition stage

Fully understand the problem and why it matters

If you want to understand or depict data across geography, use a

Geographical map

is particularly well suited to visual displays of information.

Here's What happened story

the early story you tell about your analysis—are simply educated guesses about what variables really matter in your model.

Hypothesis

A systematic approach to assessing a tentative belief (claim) about reality. It involves confronting the belief or claim with evidence and deciding, in light of this evidence,

Hypothesis Testing

Barbara McClintock, an American scientist, was named a 1983 Nobel Laureate for her discovery of genetic transposition. Her description of her work process on page 137 is an example of the creative stage called

Immersionn

Regarding the four stages of creative analytical thinking, the stage that focuses on internalization of the problem into the subconscious mind, with unusual connections likely to be made below the level of consciousness is called

Incubation

A variable whose value is known and used to help predict or explain a dependent variable.

Independent variable

Regarding the four stages of creative analytical thinking, the stage that focuses on the big breakthrough in understanding how the problem can be solved through quantitative analysis is called

Insight

The process where the software fits models to the data in an automated and rapid fashion to find the best fit is called

Machine Learning

is particularly well suited to organizations like retailers (that have a lot of stores) and banks (that have a lot of branches). That makes it easy to try things out in some locations and use others as controls.

Mad scientist story

measures of central tendency

Mean and Median

These variables have numbers with standard units, such as weight in pounds or kilograms, or height in inches or centimeters. The higher the number, the more of that variable is present. Numerical variables, then, are well suited to common statistical approaches like correlation and regression analysis.

Numerical (interval and ratio) variables

another prescriptive technique, attempts to identify the ideal level of a particular variable in its relationship to another

Optimization

These variables have numbers assigned to them, and the higher the number, the more of the variable is present. However, the difference between 1 and 2 may not be the same as the difference between 5 and 6. Atypical example of ordinal variables is the Likert item—named after the sociologist Rensis Likert— that typically involves survey responses such as strongly disagree, somewhat disagree, neither disagree nor agree, somewhat agree, strongly agree.

Ordinal Variables

is all about anticipating what will happen in the future

Prediction story

go beyond merely describing the characteristics of the data and the relationships among the variables (factors that can assume a range of different values); they use data from the past to predict the future.

Predictive analytics

Regarding the four stages of creative analytical thinking, the stage that focuses on doing the groundwork on the problem is called

Preparation

including methods such as experimental design and optimization, go even further. Like a prescription from a doctor, they suggest a course of action.

Prescriptive analytics

to show you how quantitative analysis works—even if you do not have a quantitative background—and how you can use it to make better decisions

Primary Goal of Keeping Up With the Quants

6 steps of quantitative analysis

Problem recognition, Data Collection Modeling, Data Analysis, Results Presentation and Action, Review of Previous Findings

are often useful tools for exploratory research—the earliest stage of analytics.

Qualitative Analytics

refers to the systematic empirical investigation of phenomena via statistical, mathematical, or computational techniques. Structured data is collected from a large number of representative cases and analyzed statistically.

Quantitative Analytics

The most popular measure of how well an estimated regression line fits the sample data on which it is based. It also indicates the amount of variability of the dependent variable accounted for by the regression line.

R^2

Any statistical method that seeks to establish an equation that allows the unknown value of one dependent variable to be estimated from the known value of one or more independent variables.

Regression

Choose the correct category: The numbers presented to you should be relevant to the question to which they are applied, and representative of the group or entity they supposedly represent. If the numbers do not give some answer to the question, they are merely meaningless.

Relevance

Which of the following is not one of the common steps involved in the problem recognition stage as it applies to stakeholders?

Selecting chart types

Among all the sample results that are possible when the null hypothesis is true, the (arbitrary) maximum proportion of these results that is considered sufficiently unusual to reject the null hypothesis is called the significance level.

Significance level or alpha

The use of quantitative analysis shown in the movie Moneyball is an example of how data analysis is used in the _______ industry.

Sports

If you want to show the rise and fall of one variable in relation to another (typically time), use a

Stack Graph

If you want to analyze text frequencies, use a

Tag Cloud

The essence of creative data analysis is

finding a pattern among the variables in the data.

Who said "Genius is ninety-nine percent perspiration and one percent inspiration."

Thomas Edison

To see the parts of a whole and how they relate to each other, use a

Tree Map

Analytics can be classified as qualitative or quantitative according to the process employed and the type of data that are collected and analyzed.

True

The analytical thinking example, The Suspicious Husband, is an example of

Type 1 error

The most successful analysts are those who can "tell a story with data."

Yep

Choose the correct category: If the numbers are relevant but not accurate, you need to discard them. The accuracy of numbers can be evaluated by questioning who and how they made them. Numbers that do not pass your credibility tests are useless.

accuracy

Choose the correct category: Even when accurate, numbers can often be misleading if there is represented. Especially people who have an ulterior agenda are apt to mislead with numbers intentionally.

correct interpretation

If you are only trying to relate a couple of things that can be measured numerically, you will probably want to use some type of __________________. This is one of the simplest statistical analyses you can perform. Basically it assesses whether two variables—take the weight and height of a series of people, for example—vary together.

correlation analysis

Which of following is not a concept that any executive needs to understand?

creating visualizations

Analytics can be classified as _________ according to their methods and purpose

descriptive, predictive, or prescriptive

The type of products that a customer has bought from us in the past year is the best guide to what e-mailed offers he or she will respond positively to in the future

good example of testable hypotheses.

Which of the following is not what quantitative analysts should expect of business decision makers?

ignore things you don't understand and move on

Regarding the four stages of creative analytical thinking, the stage that focuses on Intense engagement in solving the problem and the data at hand; a long struggle to find a solution takes place is called

immersion

is a purposefully simplified representation of the phenomenon or problem.

model

Wine quality = 12.145 (a constant) + .0238 vintage age + 0.616 average growing season temperature - 0.00386 harvest rainfall + 0.00117 winter rainfall

multiple linear aggression

According to the text, many Internet-based organizations—Google, Facebook, Amazon, eBay, and others—are using so-called big data from online transactions not only to support decisions but to create _________________.

new product offerings and features for customers

Good quantitative thinkers (and organizations that want to nourish them) should always demand __________ when someone presents ideas, hunches, theories, and casual observations

numbers

A key aspect of thinking quantitatively is understanding the laws of

probability and randomness

When performing a hypothesis test, the ______ gives the probability of data occurrence under the assumption that H0 is true.

p-value

Which of the following is not a best practice to becoming a quantitative analyst

social media

A test statistic that tests whether the means of two groups are equal, or whether the mean of one group has a specified value.

t-test or student's test

occurs when the null hypothesis is true, but it is rejected. In traditional hypothesis testing, one rejects the null hypothesis if the p-value is smaller than the significance level

type 1 error or alpha_error

According to the book, what is a quick and efficient way to find the concepts related to numbers that you don't know?

use a search engine