Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Statistics > Introduction to statistics > Flashcards

Introduction to statistics Flashcards

1
Q

What is a statistical unit?

A

A statistical unit is something you get a measurment from, eg. If you are doing a study on the height of 200 people, then each person you get a height value for is a statistical unit

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Why is it important to know what a statistical unit is?

A
  • When doing studies, our analysis are created on statistical units and the number of observations
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

How would you create a statistical unit for a study?

A
  • Create a list of all possible measurements to be taken for the study
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What are some examples of measurements from statistical units?

A

If the statistical units are people:

  • Age (years)
  • Gender
  • Height (cm)
  • Time to get to uni (minutes)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

If a scientist measured the height, age and weight of 200 statistical units, what would these measurements be called collectively?

A

The height, age and weight of the statistical units would be known as the observations about a variable.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

What is the difference between a variable and a variate?

A

A variable describes the measurement where as a variate is the actual value of a measurement.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Mark is 20 years old, he is 182 cm tall and he takes 23 minutes to get to uni. What is the statistical unit and what are the observations?

A
  • Mark is the statistical unit

- His age, height and the time it takes him to get to uni are the observations.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What is the reason we collect data?

A

Data is collected to prove an idea or a theory and to make comparisons.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What is statistics ?

A

It is a science that is concerned with the processing, analysis and description of data.
Collecting, presenting and transforming data to assist decision-makers

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is a population in statistics?

A

A population consists of ALL the members of a group about which you want to draw a conclusion

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What is a sample?

A

A sample is the portion or subset of the population selected for analysis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What is a parameter in statistics?

A
  • A parameter is a numerical measure that describes a characteristic of a population
  • A summary value that represents some feature of a population.
  • The value of a parameter is constant for the population and has no error associated with it.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is a statistic?

A
  • A statistic is a numerical measure that describes a characteristic of a sample
  • If the population is sampled, parameters must be estimated by a corresponding statistic.
  • Statistics are associated with a certain level of uncertainty or error.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Give an Example of a parameter.

A

The population mean student grade for Biology in 2002

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Give an example of a statistic.

A

The average student grade for the sample of students in Biology in 2002.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What is a variable?

A
  • The property of, or observation made on, a statistical unit (SU) within a population (or sample).
  • The value of this property will vary from SU to SU.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Give an example of a variable.

A
  • The student’s grade for Biology in 2002.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

What is a variate?

A

A particular value of a variable

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Give an example of a variate.

A
  • Student five had a grade of 75% for Biology in 2002.
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

What are the two branches of statistics?

A
  • Descriptive Statistics

- Inferential statistics

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

What is Descriptive statistics?

A
  • A descriptive statistic is a summary statistic that quantitatively describes or summarises features of a collection of information
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

What types of data are used in Descriptive statistics?

A
  • Collective data (Surveys)
  • Present data (Tables and Graphs)
  • Characterise data (Sample mean)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

What is Inferential statistics?

A

Drawing conclusions about a population based on sample data i.e. estimating a parameter based on a statistic

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

What data and/or techniques are used in Inferential statistics?

A
  • Estimation

- Hypothesis testing

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

Give an example of Estimation

A

Estimate the population mean weight (parameter) using the sample mean weight (statistic)

26
Q

Give an example of Hypothesis testing

A

Test the claim that the population mean weight is 100 kilos

27
Q

What is the general process of statistics?

A

Theory–>Question to answer it/Hypothesis to test –>Design Research Study –>Collect Data (measurements, observations) –>Organise and make sense of the numbers using either descriptive or inferential statistics

28
Q

What are some important sources of data collection?

A
  • Data distributed by organisation or individual
  • Designed experiment
  • Survey
  • Observational study
29
Q

What are the sources that data can be classified as?

A
  • Primary sources – Experimental Design, Conduction of a survey or an observational study
  • Secondary sources: Mostly government or industrial, but also individual sources
30
Q

What are the two types of data?

A
  • Categorical (Qualitative)

- Numerical (Quantitative)

31
Q

What is Numerical data

A

Numerical data is measured on a natural numerical scale for example:

  • Age
  • Weight
  • Temp
32
Q

What is Categorical data?

A

Categorical data can only be named or categorised, for example:

  • Gender
  • Satisfaction with a meal (very good, good, average, …)
  • Level of education (primary, secondary, tertiary)
33
Q

What are the two types of Categorical data?

A
  • Ordinal

- Nominal

34
Q

What does “Bias” mean in statistics?

A

The difference between the sample value and the true population value

35
Q

What is nominal data?

A
  • A type of Categorical data
  • No natural or implied order
  • Example - Mode of transport to uni today - car, bus, etc
  • No response is considered better
36
Q

What is Ordinal data?

A
  • A type of Categorical data
  • There is an implied order
  • Example – Rating a meal –>Good, very good, etc
  • Definite order
37
Q

What are the two types of numerical data?

A
  • Continuous

- Discrete

38
Q

What is continuous data?

A
  • A type of numerical data
  • Data that can take on any real number
  • Measured characteristics (infinite number of items)
  • Example – Time to travel to work –>53.234 minutes
39
Q

What is Discrete data?

A
  • A type of Numerical data
  • Countable number of responses (finite number of items)
  • Tends to be integer value (0, 1, 2, 3, …., 999)
  • Example number of students in today’s lecture (Can you have half a person?)
40
Q

What is the independent variable?

A
  • The variable(s) considered to be the cause of the change in the dependant variable.
  • Implies cause and effect.
  • Aka the explanatory variable(s).
41
Q

How do you know what data is the independent variable?

A
  • In regression, it is the variable (continuous or quantitative) used to predict the dependent variable.
  • In experimental designs (ANOVA) it is the variable (ordinal or nominal) that is manipulated in the experiment.
42
Q

What is the dependant variable?

A
  • The variable assumed to be influenced (or affected) by the independent variable.
  • Implies cause and effect.
  • Also called the variable of interest.
43
Q

Give an example of a dependant variable?

A

ANOVA - In an experiment to monitor growth rates in plants (dependent variable), fertiliser rates (independent variable) were manipulated.

44
Q

What are Extraneous variables?

A

All the other variables that are not of direct interest but which may have some impact.

45
Q

What is a Controlled Variable?

A
  • An extraneous variable that has been manipulated so that the impact is eliminated and any effect will be constant for each Statistical Unit (case or observation).
46
Q

What are Irrelevant Variables?

A

Variables having no effect on the study.

47
Q

What are Confounded Variables?

A
  • The researcher does not control these variables. Usually not known to the researcher and may be having a differential effect on the values of variable of interest.
48
Q

How do Confounded Variables affect the study?

A
  • These variables are confounded or interrelated with the variables under study. This may distort the studies findings.
49
Q

What are Lurking Variables?

A
  • Variable A seems to vary with variable B but this relationship is due to variable C affecting both A and B.
50
Q

What is the first step of Data Analysis?

A
  • Integrate the statistics into the process of scientific investigation.
51
Q

What is the second step of Data Analysis?

A
  • Statistical tests should be considered very early in the process and not left until the end.
52
Q

What is the third step of Data Analysis?

A
  • Decide what the question is – what is the variable of interest, what is the research question.
53
Q

What is the fourth step of Data Analysis?

A
  • Formulate a question (or hypotheses).
54
Q

What is the fifth step of Data Analysis?

A
  • Design the experiment (or sampling routine) so that you can test the hypotheses.
55
Q

What is the sixth step of Data Analysis?

A
  • A pilot study or the collection of ‘dummy’ data can aid in your investigations.
56
Q

What is the seventh step of Data Analysis?

A
  • Use the key, that we will develop throughout this course and ‘Applied Statistics’ to select an appropriate test.
57
Q

What is the eighth step of Data Analysis?

A
  • Carry out the test using the ‘dummy’ or pilot data – input data, use SPSS and interpret the output.
58
Q

What is the ninth step of Data Analysis?

A
  • If there are no problems continue, or else redesign the experiment.
59
Q

What is the tenth step of Data Analysis?

A
  • Carry out the experiment, test the ‘real’ data and write up the results.
60
Q

What are the eight things that you need to find when faced with a study or experiment?

A
  • The variable of interest (Dependent)
  • This variable’s type and scale
  • The explanatory variable(s) (Independent)
  • The type and scale of these variables
  • The statistical unit
  • The population
  • The sample
  • The aim of the experiment (research question)

Statistics (8 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions