Non coding fundamentals

Question 1

Frequentist probability

Answer 1

An interpretation of probability as describing how often a particular outcome would occur in an experiment if that experiment were repeated over and over.

Question 2

Bayesian probability

Answer 2

An interpretation of probability as describing how likely an observer expects a particular outcome to be in the future, based on previous experience and expert knowledge.

Question 3

Prior probability

Answer 3

Also called the prior, the probability based on previous experiences, according to the Bayesian approach

Question 4

Randomness

Answer 4

An apparent lack of pattern predictability in events

Question 5

Random sampling

Answer 5

The process of sampling a subset of subjects at random, such that the sample is reflective of the greater population

Question 6

Selection bias

Answer 6

Systematic differences between the sample and the population

Question 7

Normal distribution (Gaussian)

Answer 7

A probability distribution in which most values cluster in the center of the range, with the rest tapering off symmetrically to the left and right.

Question 8

Bernoulli distribution

Answer 8

A probability distribution that counts the number of successes when an event with two or more distinct possible outcomes is repeated many times

Question 9

Gamma distribution

Answer 9

A probability distribution that represents the time until an event, when the event starts out unlikely, becomes more likely and then becomes less likely again

Question 10

Conditional distribution

Answer 10

A distribution that indicates the probability that a randomly selected item in a subpopulation has a given characteristic

Question 11

Poisson distribution

Answer 11

A probability distribution that represents the number of times that a given event will occur during a given time interval.

Question 12

central limit theorem

Answer 12

The proposition that the sampling distribution of the sample means of any variable will be normal if the sample size is large enough

Question 13

Null hypothesis

Answer 13

Hypothesis that proposed that no statistically significant difference exists between two specified populationse

2.11.1

Question 14

Alternative hypothesis

Answer 14

Hypothesis that proposes that a statistically significant difference does exist between specified populations

2.11.1

Question 15

p-value

Answer 15

The probability of obserrving a sample statistic at leastt as extreme as the one that you have, assuming that the null hypothesis is true.

2.11.1

Question 16

Confidence interval

Answer 16

A statistical range with a specified probability that a given parameter lies within the range

2.11.1

Question 17

t-statistic

Answer 17

Ratio of the departure from parameter value to hypothesized value due to standard error

Question 18

independent-samples

Answer 18

a testt that compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different

Question 19

Kutrtosis

Answer 19

Measure of the sharpness of a distribution’s peak

Question 20

Skewness

Answer 20

Measure of the degree of asymmetry of a distribution

Question 21

Lean startup methodology

Answer 21

An approach that aims to introduce research-driven techniques into the core of a company’s business model

Question 22

Ceteris Paribus

Answer 22

Latin for “all other things held equal”; the assumption that every variable except the treatment variable is held equal between groups

Question 23

Control group

Answer 23

The group of test subjects left untreated to some change, then compared with treated subjects in order to validate the results of the change

Question 24

Control variable

Answer 24

a variable that the researcher controls (holds) constant during an experiment, so as to avoid biased results

Question 25

Random sampling

Answer 25

The process of sampling a subset of subjects at random, such that the sample is reflective of the greater population

Question 26

Treatment group

Answer 26

The group to which some treatment is given

Question 27

Simpson’s paradox

Answer 27

Also called the lurking variable problem, the phenomenon when an average over several groups shows one trend, but an average for each individual group shows the opposite trend or no trend.

Question 28

Indeprendent variable

Answer 28

The variable being changed or controlled to test the effect on the dependent variable

Question 29

Dependent variable

Answer 29

The variable being tested and measured in a scientific test

Question 30

Parametric test

Answer 30

A test that uses some known set of parameter estimates (such as mean and standard deviation) to represent the information in the data; this type of test works only on variables with mathematically understood distributions

Question 31

Nonparametric test

Answer 31

A test that relies on estimates that represent certain pieces of information within a variable, but not the whole variable; this type of test is appropriate for variables that don’t conform to a distribution type

Question 32

Shapiro-Wilk test

Answer 32

A nonparametric statistical test used to infer whether a variable disruption is significantly different from a normal distribution

Question 33

Wilcoxon signed-rank

Answer 33

The nonparametric equivalent of the paired t-test, for samples that aren’t normally distributed; this test uses ranked values to test whether the difference in pairs follows a symmetric distribution around zero.

Question 34

Paired t-test

Answer 34

A test used to compare two dependent (or paired) groups

Question 35

Tukey’s honest significant differences

Answer 35

Also called Tukey’s HSD test, a parametric statistical test that compares all possible pairs of means and uses a variability estimate based on variability from all the groups combined

Question 36

Kruskal-Wallis test

Answer 36

A nonparametric statistical test that whether samples originate from the same distribution

Question 37

One-way analysis of variance

Answer 37

One-way ANOVA, a parametric statistical test used to compare whether two samples means are significantly different

Question 38

Type I error

Answer 38

Also called a false positive, rejection of a true null hypothesis

Question 39

Type II error

Answer 39

Also called a false negative, failure to reject a null hypothesis