Data Analytics: CH - 5(UNFINISHED SLIDE 10 CONTINUE)

How is analytics perfomred

They are usually dependent on the question that needs to be answered

REMEBER: 4 Types of Data Analytics

Descriptive, Diagnostics, Predictive, Prescriptive

Define: Descriptive Analytics

Characterizes, summarizes and organizes features and the properties of the data to facilitate understanding of the results and the underlying data

What questions does Descriptive Analytics address?

What happened? What is happening?

In what data sources does descriptive analytics shine?

1.) Financial Statements,

2.) Internal information systems(HRMS, CRM, supply chain systems)

3.)External Sources

Name all Statistical and Summarization Tools

Counts, Totals(sums avg, subtotals), Mns/Max/med and standard deviations Graphs, Horizontal and vertical analysis, Ratio analysis

Define: Diagnostic Analytics

Performed to investigate the underlying cause that cannot be answered by simply looking at the descriptive data

What questions does Diagnostic Analytics address

Why did it happen? What are the reasons for the past result? Can we explain why it happened?

What are the two broad categories of diagnostic analytics?

Identify anomalies/outliers & Find previous unknown linkages, patterns or relationships between & among variables

Define: Anaomalies/Outliers

Unusual and/or unexpected results or transactions

Define: Benfords Law

In any large, randomly produces set of natural numbers there is an expected distribution of the first digit(most common 1st digit is 1,2,3 etc)

What is considered an anomaly

If a distributions departs from that expectation it is considered an anomaly and should be investigated

Other examples of Outliers and Anomalies

1.) Internal control testing 2.) Fuzzy matching 3.) Sequence checks 4.) Duplicate transactions 5.) Variance analysis 6.) cash and bank reconciliations

How do you find previously unknown linkages patterns or relationships?

Perform Drill down Analytics

Define: Drill down Analytics

Used to uncover details in the data by looking at different levels of the data to understand why something happened

How are cross - tabulations used?

to view transactions from different perspective

What are the uses of Perform Drill down analytics

Look for patterns to identify potential correlations quantitatively analyze relationships among wo or more variables, data sorting and manipulation

Determine relations/patterns/linkages/between variables

correlation, regression, hypothesis testing

Define: Predictive Analytics

Performed to provide foresight by identifying patterns in historical data and assessing the likelihood or probability. Predict future performance based on statistical techniques

What questions does Predictive Analytics Address?

Will it happen in the future? What is the probability something will happen? Is it forecastable?

Five Broad Categories of Prescriptive Analytics

1.) Sensitivity Analysis

2.) Capital Budgeting

3.)Marginal(incremental) analysis

4.) Goal Seek Analysis

5.) What-if scenario analysis

Define: Sensitivity Analysis

Evaluate outcomes based on uncertainty regarding the inputs

Define: Capital Budgeting

Evaluating future cash flows for potential investments EX: net present value & Internal rate of return

Define: Marginal(Incremental) Analysis

Used to determine the change in profit in associated with the cost or benefit of the next unit produced

Define: Goal-Seek Analysis

What-if anaylsis that tells what needs to be done to reach a desired outcome

Define: What-if scenario analysis

Analysis of potential future events by considering potential outcomes

Define: Population

Group phenomenon having something in common

Define: Sample

A subset of members of a population selected to represent that population should be representative of the population

Define: Parameter

A characteristic of a population mean of the population is µ

Define: Statistic

A characteristic of a sample; mean of the sample x ̅

Mean

sum of all data points divided by the number of data points

Median

midpoint of the data in a sorted array

Mode

observation that occurs most frequently

Range

the difference between maximum and minimum values

Variance

average of square differences from the mean

Standard Deviation

square root of variance

What items describe the spread(variability of the data

Range Variance Standard Deviation

NOTE TO REMEMBER

NOTE: The greater the standard deviation or the variance the greater the variability within the sample

Probability Distributions

Statistical property that describes the possible values of random variables and the likelihood that a random variable will be within a given range

Name the 3 primary probability distributions

Normal Distribution, Uniform Distribution, Poisson Distribution

Define: Normal Distribution

A bell shaped probability distribution that is symmetric about the mean with data points closer to the mean more frequent than those farther from the mean

Define: Z-Score

tells how many standard deviations a data point is from the mean

Data within 1 standard deviations includes what % of data

68%

Data within 2 standard deviation includes what % of data

95%

Data within 3 standard deviations includes what % of the data

99.7%

Define: Uniform Distribution

a probability distribution where all outcomes are equally likely

Define: Poisson Distribution

a distribution characterized as the mean number of events per interval of space or time Has a low mean and is highly skewed to the right

Hypothesis

is an assumption or theory based on an understanding of the data

Null Hypothesis

assumes that the hypothesized relationship does not exist there is no significant difference between two samples or populations (H0 is the symn

H0