Graphs and Charts

Question 1

What are graphs and charts used for?

Answer 1

Summarizing results visually

Question 2

What do scatter graphs show us?

Answer 2

the relationship between two variables plotted on x and y axis

Question 3

What can we identify from the relationship of the two variables shown on a scatter graph?

Answer 3

correlational trends, e.g. height and weight are positively correlated

Question 4

What is a coefficient used for?

Answer 4

To measure the strength and direction of correlations

Question 5

What do coefficients range from?

Answer 5

+1.0 to -1.0

Question 6

what would a coefficient of ….. mean?

-0.3
-0.8
+0.3
+0.8

Answer 6

Weak Negative
Strong Negative
Weak Positive
Strong Positive

Question 7

What can correlational interpretations not predict?

Answer 7

Cause and effect

Question 8

What are correlational coefficients used for?

Answer 8

Bi-variant data

Correlational analysis

Question 9

What type of data is a bar graph used for?

Answer 9

Univariant data

Question 10

What does a bar graph show?

Answer 10

The frequency of data

Question 11

A bar graph is the best way of displaying….what?

Answer 11

nominal data that has been collected into categories

Question 12

What does the highest bar of bar graph show?

Answer 12

Modal variable

Question 13

A gap in the bar means the data is… ?

Answer 13

categorical/nominal data

• Means no link across x axis
• Known as discreet data

Question 14

Strength of a bar graph

Answer 14

You can compare multiple categories on one chart

Question 15

What is a histogram?

Answer 15

Very similar to a bar graph but for frequency of data = CONTINUOUS DATA
No gaps in bars shows continuous relationship scale

Question 16

Strengths of a frequency polygon, made from a histogram (2)

Answer 16

better for showing trend of continuous data

Still be used to compare multiple sets of data

Question 17

Interpreting significance: what does p≤0.005 mean?

Answer 17

The probability that the results actually occurred by chance are 5% or less so the results are significant

Question 18

What does p>0.005 mean?

Answer 18

Means the probability of the results happening by chance are grater than 5% so the results are not significant

Question 19

What is a Type 1 error?

Answer 19

A Type I Error is also known as a False Positive or Alpha Error. This happens when you reject the Null Hypothesis even if it is true. The Null Hypothesis is simply a statement that is the opposite of your hypothesis. For example, you think that boys are better in arithmetic than girls. Your null hypothesis would be: “Boys are not better than girls in arithmetic.”

You will make a Type I Error if you conclude that boys are better than girls in arithmetic when in reality, there is no difference in how boys and girls perform. In this case, you should accept the null hypothesis since there is no real difference between the two groups when it comes to arithmetic ability. If you reject the null hypothesis and say that one group is better, then you are making a Type I Error.

Question 20

What is a Type 2 error?

Answer 20

A Type II Error is also known as a False Negative Error. This happens when you accept the Null Hypothesis when you should in fact reject it. The Null Hypothesis is simply a statement that is the opposite of your hypothesis. For example, you think that dog owners are friendlier than cat owners. Your null hypothesis would be: “Dog owners are as friendly as cat owners.”

You will make a Type II Error if dog owners are actually friendlier than cat owners, and yet you conclude that both kinds of pet owners have the same level of friendliness. In this case, you should reject the null hypothesis since there is a real difference in friendliness between the two groups. If you accept the null hypothesis and say that both types of pet owners are equally friendly, then you are making a Type II Error.