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Question 1

What is Statistics?

Answer 1

Statistics is the science of collecting, organizing, presenting and interpreting numerical facts, which we call data.

Statistics is the science of learning from data.

Question 2

What can Statistics do?

Answer 2

Statistics can:
* Explore and visualize large and complicated datasets
* Compress data to extract useful information
* Create models for real-world problems
* Estimate and predict unknown parameters or quantities
* Test research questions and hypotheses.

Question 3

Why learn Statistics?

Answer 3

Reasons to learn statistics include:
* Solving your own statistical problems
* Understanding statistical methods in scientific papers
* Being comfortable and competent around data and uncertainty.

Question 4

What are the two categories of Statistics?

Answer 4

The two categories of Statistics are:
* Descriptive Statistics
* Inductive Statistics.

Question 5

What is Descriptive Statistics?

Answer 5

Descriptive statistics is also referred to as empirical statistics, where data is described and summarized to gain information about the data.

Question 6

What methods are used in Descriptive Statistics?

Answer 6

Descriptive methods include:
* Pivot tables
* Graphs/charts
* Summary statistics.

Question 7

What is Inductive Statistics?

Answer 7

Inductive statistics is also referred to as mathematical statistics or inferential statistics, which estimates information about a population based on a sample.

Question 8

What is the goal of Inductive Statistics?

Answer 8

The goal of inductive statistics is to draw conclusions from a sample and generalize these conclusions to a population.

Question 9

What is Probability theory in relation to Inductive Statistics?

Answer 9

Probability theory is the foundation of inductive statistics and is used to account for uncertainty in the estimation process.

Question 10

What is Combinatorics?

Answer 10

Combinatorics is an area of mathematics important in statistics, especially in probability theory, concerning arrangements and selections of elements.

Question 11

What are primary and secondary data?

Answer 11

Primary Data: Firsthand collection of data by a researcher.
Secondary Data: Data that has already been collected by someone else.

Question 12

What are the characteristics of quality data?

Answer 12

Points to consider regarding data quality include:
* Source of data
* Availability of raw data
* Random selection of respondents
* Use of suggestive questions
* Existence of independent confirmation.

Question 13

Define empirical population.

Answer 13

An empirical population is a finite set of N objects that are clearly defined.

Question 14

What is a sample in statistics?

Answer 14

A sample is a (random) selection of n objects from a population.

Question 15

What is an observational unit?

Answer 15

An observational unit is an entity whose characteristics are measured.

Question 16

What is an attribute in statistics?

Answer 16

An attribute is a characteristic or feature measured for each observational unit.

Question 17

What is the difference between parameter and sample statistic?

Answer 17

Parameters are the true values of a population, while a sample statistic is a variable representing information based on a sample.

Question 18

What are the levels of measurement in statistics?

Answer 18

Levels of measurement include:
* Nominal data
* Ordinal data
* Quantitative data.

Question 19

What is nominal data?

Answer 19

Nominal data consists of categories with no meaningful order.

Question 20

What is ordinal data?

Answer 20

Ordinal data has a meaningful order, allowing for ranking.

Question 21

What is quantitative data?

Answer 21

Quantitative data is observed, counted, or measured and involves numbers with a scale unit.

Question 22

Fill in the blank: Statistics is the science of ______.

Answer 22

collecting, organizing, presenting and interpreting numerical facts.

Question 23

True or False: Inductive statistics can be used to make predictions about a population based on a sample.

Answer 23

True

Question 24

What is the meaning of ‘natural objective’ in data analysis?

Answer 24

It refers to the possibility of ranking data in a meaningful order for analysis.

Question 25

What type of data is described as 'quantitative metric data'?

Answer 25

Data that is observed, counted, or measured with a scale unit.

Question 26

Define quantitative-discrete data.

Answer 26

Data that can only take values from a fixed list of numbers.

Question 27

What is quantitative-continuous data?

Answer 27

Data that can take any value from a continuum on the number line.

Question 28

What is the nominal scale in the Level of Measurement?

Answer 28

A scale where attribute values can be sorted but distances are not quantifiable.

Question 29

What distinguishes an ordinal scale from a nominal scale?

Answer 29

An ordinal scale allows for ranking of attribute values, while a nominal scale does not.

Question 30

What is a metric scale?

Answer 30

A scale where both sorting and quantifiable distances are possible.

Question 31

What is the difference between an interval scale and a ratio scale?

Answer 31

An interval scale has a subjectively defined zero point, while a ratio scale has an objectively defined zero point.

Question 32

What does 'observational unit' refer to?

Answer 32

An object of a population or sample that is observed.

Question 33

What type of data is characterized as 'multivariate data'?

Answer 33

Data that records and analyzes multiple pieces of information about an object simultaneously.

Question 34

What is 'raw data'?

Answer 34

The original uncompressed recording of all information regarding a population.

Question 35

Define stock data.

Answer 35

Data measured at one specific time point representing a quantity at that time.

Question 36

What is flow data?

Answer 36

Data measured over an interval of time.

Question 37

What is the difference between extensive data and intensive data?

Answer 37

Extensive data leads to useful information when summed, while intensive data requires averaging to obtain useful information.

Question 38

Define absolute frequency.

Answer 38

The number of times a specific attribute value occurs in a population of size N.

Question 39

What is relative frequency?

Answer 39

The absolute frequency of a specific attribute value divided by the total population size N.

Question 40

What does cumulative frequency represent?

Answer 40

The sum of the absolute frequencies of all attribute values less than or equal to a specific attribute value.

Question 41

In cumulative frequency, what is relative cumulative frequency?

Answer 41

It is the cumulative frequency divided by the total number of events.

Question 42

Fill in the blank: A nominal scale can handle _______ but not quantifiable distances.

Answer 42

sorting

Question 43

True or False: An ordinal scale allows for both sorting and quantifiable distances.

Answer 43

False

Question 44

Fill in the blank: The zero point in a ratio scale is defined _______.

Answer 44

objectively

Question 45

What is the total weight of all Google employees in 2024?

Answer 45

Approximately 13.9 million kilograms.