Data Collection

Question 1

Design points for a survey

Answer 1

• make all questions clear don’t use technical jargon
• make sure each question only asks about one issue
• make questions as short as possible
• avoid negative items as they can confuse respondent
• avoid biased items and terms
• use a consistent response method such as a scale of 1 to 7 or yes or no
• sequence questions from general to specific
• make the questions as easy to answer as possible
• Define any unicorn usual terms for example when you were conducting a survey about open space zoning be sure to define what the term means

Question 2

3 steps for the statistical process

Answer 2

1. collect data (ie surveys)
2. Describe and summarize the distribution of the values
3. Interpret by means of inferential statistics and statistical modeling. (Ie draw general conclusions for the population based of the sample)

Question 3

Types of measurement

Answer 3

1. nominal data
2. Ordinal data
3. Interval data
4. Ratio data

Question 4

Types of variables

Answer 4

1. Quantitative
2. Qualitative
3. Continuous
4. Discrete
   4a. Binary
   4b. Dichotomous

Question 5

Nominal data

Answer 5

Nominal data are classified at a mutually exclusive groups or categories and lack intrinsic order.

Zoning classification, Social Security number, and sex are examples of nominal data

Question 6

Ordinal data

Answer 6

Ordinal data are ordered categories implying a ranking of the observations.

Even though ordinal data maybe give a numerical values such as 1, 2, 3, 4, the values themselves are meaningless, only the rank counts. So, even though one might be tempted to infer that 4 is twice 2, that is not correct. Examples of ordinal data or letter grades suitability for development in response scales on a survey

Question 7

Interval data

Answer 7

Interval data is data that has an ordered relationship where the difference between the scales has a meaningful interpretation.

The typical example of interval data is temperature, where the difference between 40 and 30° is the same as between 30 and 20°, but 20° is not twice as cold as 40°

Question 8

Ratio data

Answer 8

Ratio data is the gold standard of measurement we’re both absolute and relative differences have a meeting.

The classic example of ratio data is a distance measure, where the difference between 40 and 30 miles is the same as the difference between 30 and 20 miles, and in addition, 40 miles is twice as far as 20 miles

Question 9

Continuous variables

Answer 9

Continuous variables can take an infinite number of values, both positive and negative, and with as find a degree of precision as desired.

Question 10

Discrete variables

Answer 10

Discrete variables can only take on a finite number of distinct values. An example is the count of the number of events, such as the number of accidents per month.

Question 11

Binary and dichotomous variables

Answer 11

A special case of discreet variables

Question 12

Inferential statistic

Answer 12

Inferential statistics his probability Siri to determine characteristics of a population based on observations made on a sample from the population.

Question 13

Distribution

Answer 13

Distribution is the overall shape of all observed data.

Question 14

Gaussian distribution

Answer 14

The normal bell curve.
This distribution is symmetric and has the additional property that the spread around the mean can be related to the proportion observed.

Question 15

Symmetrical distribution

Answer 15

An equal number of observations are below and above the mean. (This is the case for normal distribution)

Question 16

Skewed

Answer 16

More observations below the mean or more about the mean.

Question 17

Skewed to the right

Answer 17

When the bulk of the values are about the mean.

Question 18

Skewed to the left

Answer 18

Small values (such as zero) pull the distribution to the left.

Question 19

Central tendency

Answer 19

Typical or representative value for the distribution of observed values.

Measurements of central tendency are mean, median and mode.

Question 20

Mean

Answer 20

Is the average distribution

Question 21

Media

Answer 21

Is the middle value of a ranked distribution.

Question 22

Mode

Answer 22

Is the most frequent number in the distribution.

Question 23

Coefficient variation

Answer 23

Measured the relative dispersion from the mean by taking the standard deviation and dividing by the mean.

Question 24

Z-score

Answer 24

This is the standardization of the original variable by subtracting the mean and dividing by the standard deviation.

Question 25

Inter-quartile range or IQR

Answer 25

An alternative measure of dispersion.

IQR forms the basis for an alternative concept of outliers. Two fences are computed as the first quartile less 1.5 times the IQR and the third quartile plus 1.5 times the IQR. Observations that are outside these fences are termed outliers. This is visualized in a box plot aka box and whiskers plot.

Question 26

Statistical inference

Answer 26

The process for drawing conclusions about the characteristics of a distribution from a sample of data.

Question 27

Hypothesis test

Answer 27

A statement about a particular characteristic of a population.

Question 28

Null hypothesis

Answer 28

Point of departure or reference.

Question 29

Alternative hypothesis

Answer 29

The research hypothesis one wants to find support for by rejecting the null hypothesis.