Qm - Module 1 - Introducing Statistics

Front 1

What are the two parts of Statistics?

Back 1

descriptive and inferential statistics

Front 2

What is descriptive statistics?

Back 2

this element handles the problem of sorting a large amount of
collected data in ways which enable its main features to be seen immediately.

Front 3

What is inferential statistics?

Back 3

This element
tackles the problem of how the small amount of data that has been collected (called
the sample) may be analysed to infer general conclusions about the total amount of
similar data that exist uncollected in the world (called the population).

Front 4

Define probability

Back 4

Probability is a way of quantifying
the strength of belief in the information derived and the conclusions drawn.

Front 5

Name the methods of measuring Probability

Back 5

A priori approach
Relative frequency approach
Subjective approach

Front 6

Describe a priori approach to measuring probability.

Back 6

the probability of an event is calculated
by a process of logic. No experiment or judgement is required. Probabilities
involving coins, dice, playing cards etc. can fall into this category.

Front 7

Describe relative frequency approach to measuring probability.

Back 7

When the event has been or can be repeated a
large number of times, its probability can be measured from the formula
P (event) = No. of times event occurs/No. of trials

Front 8

Describe the subjective approach to measuring probability.

Back 8

the degree of belief that an individual has about a particular event may
be expressed as a probability.

Front 9

Define data points/observations

Back 9

The measurements or values of a specific variable being evaluated.

Front 10

What is an Ordered Array? What is it used for?

Back 10

To arrange data in columns and in order. First step in organizing data.

Front 11

What is classifying mean?

Back 11

grouping the data (numbers) in bands (e.g. 50 - 54)

Front 12

What is frequency when used with classified data?

Back 12

Refers to the number of data points that fall within a particular class.

Front 13

Explain a Frequency Table?

Back 13

Classes are listed in order; frequencies are indicated for each class.

Front 14

What is a Frequency histogram?

Back 14

Taking data from Frequency Table and plotting on a graph.

Front 15

Define probability histogram

Back 15

created by taking a frequency histogram and changing the units of the vertical axis to probabilities instead of frequencies. Can also be called a distribution.

Front 16

What is a discrete variable?

Back 16

a variable that is limited in the values that it can take.

Front 17

What is a discrete distribution?

Back 17

the variable is distributed across a range of values; it is discrete because the values the variables take are in steps rather than smoothly following one another.

Front 18

What is a continuous variable?

Back 18

A variable that is not limited in the values that it can take. It does not group data in classes.

Front 19

What is a continuous distribution?

Back 19

A distribution formed by a continuous variable. An extension of a discrete distribution.

Front 20

List differences between discrete and continuous distributions.

Back 20

Discrete
Variable limited to certain values
Shape is usually stepped
Probabilities are equal to column heights
Sum of column heights + 1

Hint 20

Continuous
Variable not limited
Shape is usually smooth
Probabilities are equal to areas under the curve
Total area = 1

Front 21

List problemsn with use of continuous distributions.

Back 21

1. one can never collect enough data to establish continuous distribution
2. Accurate measurement of area under the curve is difficult.

Front 22

What is the difference between a Observed and Standard Distribution?

Back 22

Observed Distribution
Data were collected, a histogram formed and that was distribution

Hint 22

Standard Distribution
has a theoretical, rather than observational base. Defined mathematically from a theoretical situation.

Front 23

Unimodal distribution

Back 23

has just one hump (at the average of the variable)

Front 24

What are the two parameters of distribution curves?

Back 24

Average or mean of the distribution

Standard deviation measures the dispersion, or spread of the variable.

Front 25

Common wrong uses of Statistics

Back 25

Absence of, or not precise definitions
Graphics - graphs, can be misleading (scales)
Bias - personal bias
Omissions - leaving out pertinent info
Logical errors - conclusion errors
Technical Errors - not understanding the math

Front 26

What are the general questions that can be asked to help overcome statistical errors/trickery?

Back 26

1. Who is providing the evidence? If providor stands to gain, be careful.
2. Where did data come from? Data should be from same/similar survey, sample size, questions, environment,etc.
3. Does it pass the common sense test?

Front 27

Questions to check for common errors

Back 27

1. Is there ambiguity of definition?
2. Are graphics misleading?
3. Is there simple bias?
4. What is missing?
5. Is there a logical error?
6. Is there a technical error?