Lesson 3: Central Tendencies

Question 1

What are the three standard measures of central tendency?

Answer 1

Mean, Median, and Mode

Question 2

What is the mean? How do we find it?

Answer 2

It is the sum of all the scores divided by the number of scores in the data

Question 3

When do we use the weighted mean? What are the steps to calculate the weighted mean?

Answer 3

We use the weighted mean when the sample size is different
1. Determine the combined sum of all of the scores
2. Determined the combined number of scores
3. Divide the sum of scores by the total number of scores

Question 4

When will a mean not work?

Answer 4

When a distribution has scores closer to the extremes (will have a skewed grah)

Question 5

What are some characteristics of a mean?

Answer 5

1. Changing the value of a score in the data changes the mean
2. Introducing or removing a score changes the mean
3. Adding or subtracting a constant from each score changes the mean by the same constant
4. Multiplying or dividing each score by a constant multiplies or divides the mean by that constant

Question 6

What is the median?

Answer 6

Divides the scores so that 50% of the scores in the distribution have values that are equal to or less than the median

Question 7

T/F: The median can be used on ordinal data

Answer 7

Yes. The mean should not be used on ordinal data

Question 8

What are the pros of the median?

Answer 8

It is less affected by extreme scores and the median tends to stay in the “center” of the distribution even when there are a few extreme scores or when the distribution is very skewed

Question 9

What is the mode?

Answer 9

It is the most frequently occurring category or score in the distribution

Question 10

T/F: The mode can be determined for data measured on ANY scale of measurement (nominal, interval, ratio, etc.)

Answer 10

True

Question 11

Where would the mean, median, and mode be depending on a skewed graph?

Answer 11

Mean: will be found far toward the long tail
Median: will be found toward the long tail, but not as far as the mean
- is less affected by extreme scores
Mode: found near the peak of the data

Question 12

When is the distribution positively skewed?

Answer 12

Mean is bigger than the median
- mean is closer to the long tail

Question 13

When is the distribution negatively skewed?

Answer 13

Mean is smaller than median
- mean is closer to the long tail