IBA

business analytics

process of turning data into insights to improve business decisions

statistics

science of collecting, analyzing and interpreting data

data

any value that conveys information

KPI

key performance indicator

KRA

key result area

descriptive, diagnostic, predictive, prescriptive

4 types of analytics

data management

is the practice of collecting, protecting and storing of data, to be analyzed for business decisions

nominal

no natural rank or order

ordinal

with natural rank and order, no equal distance

interval

with natural rank and order, with equal distance, no true zero

ratio

with natural rank and order, with equal distance, with true zero

nominal and ordinal

categorical

interval and ratio

continuous

mean, median and mode

measures of central tendency

standard deviation

is a statistical measurement that shows how spread out data is in relation to its mean

low sd

values are clustered closer to mean

high sd

values are far from mean

variance

how spread out a set of values are and how far they are from average value

mediation analysis

to understand which one variable influences the other

full mediation

completely explains the relationship between IV and DV

partial mediation

partially explains the relationship between IV and DV

latent variable

cannot be measured

test of difference

used to determine whether there is a significant difference among groups

z test

t test

anova

chi square TOD

mann whitney u test

kruskal wallis h test

macnemar test

different types of TOD

independent sample t test

dependent sample t test

one sample t test

different types of t test

test of association

if a relationship between two variables exists

chi square test of independence/association

1 way anova

2 way anova

types of test of association

parametric test

assume that the data follows a specific distribution, such as a normal distribution, and focus on parameters like the mean.

non parametric test

don't assume a specific distribution and are often used when the data doesn't meet the assumptions of parametric test

traditional approach

non traditional approaching

types of hypothesis testing

non traditional approach

p-value approach, on the other hand, uses the p-value (probability) to determine whether to reject the null hypothesis

traditional approach

relies on calculating a test statistic and comparing it to a critical value or significance level to make a decision about the null hypothesis

shapiro wilk

most common test of normality

pearsons r correlation

spearman’s rho

kendall’s tau

chi square test of association

types of correlation analysis

association analysis

association between 2 variables

parametric and non parametric

2 types of statistics

macnemar test

what test do we use f data is binary

regression

asks whether there is a significant effect, impact and influence. a statistical method that tries to determine the strength and character of the relationship between one dependent variable and a series of other variables

relationship by association

casual relationship

2 types of regression relationship

dummy codes

number assigned to your data codes