Test 1

Question 1

Do the numbers make sense?
- 300 jobs were created.
- Your salary increased by 2% increase this year.

Answer 1

Not telling the whole truth.
Make sure to question the data!
- BUT, 500 people were fired
- BUT, the cost of living increased by 4%.

Question 2

What is cherry-picking?
Give an example.

Answer 2

Cherry picking is selecting only parts of the data that support a certain opinion.
A hockey team plays 25 games a season.
They lost 12 games, Tied twice, lost another two, won 7,Then lost 2
The parents get angry that the team has lost most games
The coach answered said that they have won 7 of the ten last games.

Question 3

Who collects the data?
McDonald’s made a study saying that by eating their food everyday you will help you lose weight.

Answer 3

Be wary of who is collecting the data since they could have some sort of bias
For example: pharmaceutical compagnies doing their own research on their products.

Question 4

Be wary of comparison.
EX: In July, ice cream sales increase - so do the numbers of drowning. In February, the both go down

Answer 4

Two things that happen at the same time doesn’t mean they are related

Question 5

Are the numbers consistent?
In a sample of 20 Vanier students. 57% are in social science, 27% in science and 16% in technology

Answer 5

NO. They need to be intervals of five in this situation to make sense of the numbers.

Question 6

Are the numbers consistent?
- One of my colleagues is complaining that 20% of his classes of their classes or on a Friday.
- 30% of crimes happen on the weekend (Saturday and Sunday)

Answer 6

The numbers are exactly what we think the are.
- Every school day has a 20% of classes (100% / 5days= 20%)
- (100% / 7 days = 14.28 14.28 x 2 = 30 )

Question 7

Are the numbers possible?
The average student spends 8000 hours on instagram a year.

Answer 7

• NO, average of hours in a year 8760- that would mean that students don’t sleep and don’t go to school

Question 8

Is the arithmetic right?
25% of men, 37% of women favour a 4-day work week, so 62% of people what this.

Answer 8

NO, Common errors is when adding percentages of different groups.
- Doesn’t equal to a100%.

Question 9

Are these bad calculations?
- In Canada, 64% of those over 65 years are women and only 18% are men.
- At Vanier, 54% of the students are in social students, 35% are in science, 14% in commerce, and 36% are other programs.

Answer 9

• YES, Doesn’t equal to 100%, but 82%
• YES, Doesn’t equal to 100%, but 139%

Question 10

What is a population?
Give an example.

Answer 10

A Population is all members of a group.
- All the people living in Québec
- All the students in Vanier college
- All canadiens over 18

Question 11

What is a sample?

Answer 11

A sample is a part of a population at interest.
* A sample is selected form a population.
- one thousand canadiens over 18
- ten school in the province of Alberta

Question 12

What is systematic sampling?

Answer 12

Go throught the whole population and systematically selected them.
EX: every fifth person makes is part of the sample.

Question 13

What is a cluster sample?

Answer 13

A subgroup of the whole population.
EX: all the Asian restaurants in the population of all restaurants.

Question 14

What is a stratified sample?

Answer 14

a specific type of a group within population. Could also be Proportional stratified sample if you know the amount of each group (representative of the population).
EX: 2 italian, 5 asian, 6 fast foods…

Question 15

What is convenience sampling?

Answer 15

Choosing the members of a population that are easiest to reach.
EX: The students from your class from the whole Vanier population

Question 16

What is voluntary sampling?

Answer 16

The members of your sampling are members who volunteered

Question 17

What is a sample that is representative of a population?

Answer 17

The characteristics of the population are represented in the sample.

Question 18

What is a sample that is biased of a population?

Answer 18

a sample that is biased means that the characteristics are either over of under represented.

Question 19

What is Simple Random Sampling (SRS)? (explain the process)

Answer 19

SRS gives and equal chance to all the members of population to be selected from the sample.
1) Give everyone a number (0-???)
2) Get a computer to generate a series of numbers to randomly select a number.

Question 20

What is a number that describes the population?

Answer 20

a Parameters

Question 21

What is a number that describes a sample?

Answer 21

a Statistic

Question 22

What can a parameter or a statistics be?

Answer 22

Proportion (fraction, decimal or percentage) or a mean (average)

Question 23

What are the Quantitave methods symboles for sample size, sample proportion, sample mean, Population proportion, Population mean)

Answer 23

check screen shot of table.

Question 24

What is an under-coverage sampling error?

Answer 24

When a group of a population is left out. EX: call people from a phone book for your sample, people with no phone or house is left out

Question 25

What is a convenience sampling error?

Answer 25

It excludes people who aren't convenient to you

Question 26

What is a voluntary sampling error?

Answer 26

Certain kinds of people are more likely to participate in a study.

Question 27

What is a random sampling error?

Answer 27

Even if you try to be as unbiased as possible your sample could still be baised..

Question 28

What is a leading question non-sampling error?

Answer 28

Theses are questions that are ambiguous or that lead to a specific question. EX ; "Free music steaming is like stealing. You wouldn't be oppose to a fee to stream music.

Question 29

What is a error response non-sampling error?

Answer 29

The respondent make a mistake or gives and unclear answer. EX: How much music do you listen to? A little, a lot, 5 hrs...

Question 30

What is a non-response non-sampling error?

Answer 30

Respondent don't answer to question.

Question 31

What is a processing error non-sampling error?

Answer 31

entering data and making a mistake EX: entering 100 instead of 10

Question 32

What is a variable?

Answer 32

A variable is anything that can be measured EX: age, gender, height, weather...

Question 33

What is a attribute?

Answer 33

An attribute is a characteristic of a variable. EX: what is your marital status? MARRIED, SINGLE, WIDOWED..

Question 34

What is the difference between a dependent and independent variable?

Answer 34

-Independent causes the change. -Dependant is influence by the change.

Question 35

What are the three levels of measurement and what does they measure?

Answer 35

- Nominal, attributes that cannot be ranked EX: dog cat fish... - Ordinal, can be ordered EX: cold, cool, warm and hot - Interval ratio, can be ranked and determine the difference between variables. EX; 100cm, 130cm, 150cm...

Question 36

Why is it important to present data?

Answer 36

It is important to present data visually to easily understand it and organise the data.

Question 37

Example of a frequency table? relative frequency table?

Answer 37

- Summarise the distribution of the data - How each category compares to the total.

Question 38

Example of a bar graph?

Answer 38

Shows the frequency of each attribute as a bar (don't touch)

Question 39

Example of pie chart?

Answer 39

Is a circle divided into segments, each segment is proportionate to the attribute

Question 40

Example of Histograms?

Answer 40

continuous quantitative data. (The bars touch).

Question 41

What do these words to describe a histogram mean? - Symmetrical -Skewed - Positively Skewed - Negatively Skewed - outliner

Answer 41

- The distribution on the graph is roughly a mirror image - it is not a mirror image - The bump is at the beginning - The bump is at the end - There's a little bump separated from the rest of the data.