Populations, Parameter and Interferance

Question 1

Can populations be pictured by histograms

Answer 1

No populations are not samples and therefore can’t be pictured as they are often conceptual.

Question 2

Why do we have a sample of a population

Answer 2

From a sample of a population you can make INFERENCES about the population

Question 3

How to prevent a sample bias

Answer 3

Randomly select a sample

Question 4

How to ensure validation and correct inferences

Answer 4

Need to decide how large the sample size is

Question 5

What does a normal distribution look like

Answer 5

The curve has a central peak with the curve descending SYMMETRICALLY o either side

Question 6

What does the height of the curve indicated in a normal distribution

Answer 6

The height of the curve indicates the most values of the population fall near the central value with fewer values further from the centre

Question 7

What does the symmetrical decline in a normal distribution tell us?

Answer 7

Tells us that their are equal amounts of the population located at the same distance above the peak as there is at that distance below the peak

Question 8

What is different within normal distribution?

Answer 8

The location of the data- determined by the position of the central peak
The spread of data
The dispersion of data -width of the bell

Question 9

How is the location and the dispersions of data in a normal distribution determined by

Answer 9

They are determined by two POPULATION PARAMETERS:
- Peak is located at the population MEAN
- The width is determined by the population standard deviation

Question 10

What are the population parameters in the normal distribution

Answer 10

• Mean
• Standard Deviation

Question 11

How to calculate population parameters?

Answer 11

Population parameters are unknown. There are sample analogs of population parameters and they can be estimated from sample data known as SAMPLE STATISTICS.

Question 12

How to calculate the sample mean of a distribution?

Answer 12

Adding all numbers up and dividing by number of values

Question 13

What parameters can be used of the data is not normally distributed

Answer 13

• Median
• Quartiles

Question 14

Why use a a median instead of mean for non normal distribution

Answer 14

The mean is sensitive to the values of a few LARGE OBSERVATIONS in a way median is not

Question 15

Why can’t you be too eager to jump to median and qualities>

Answer 15

-Inefficient analysis
- Unnatural analyses

Question 16

Name a method that can be used to deal with non-normal data

Answer 16

Transforming data

Question 17

The whole area underneath the bell-shaped curve equals what?

Answer 17

1

Question 18

What is the value of probability corresponding to a given X

Answer 18

It is the cumulative probability of the distribution at X or the Cumulative distribution function at X

Question 19

What is the probability that a value is above X

Answer 19

1-X

Question 20

What does Q normally represent in a normal distribution curve

Answer 20

The probability of being above an equal number of units above the mean (probability height)

Question 21

Does each X in a normal distribution curve have a corresponding P

Answer 21

Yes, P depends only on that multiple of alpha above or below the mean (Z), not on the values of u and alpha

Question 22

What is the advantage of knowing that P (Probability) depends ONLY ON THE Z-VALUE

Answer 22

It gives considerable aid to understand your data and its distribution

Question 23

Where does 95% of the values in a normal distribution lie

Answer 23

95% lie within two standard deviation of the mean

Question 24

What does the interquartile range equal for a normal distribution

Answer 24

1.36alpha

Question 25

What does the smaller sample size do to the normal distribution curve

Answer 25

There are less extremes than a larger sample size

Question 26

What does the range for a normal distribution represent

Answer 26

The spread of measurements and sample size

Question 27

Why is the normal distribution important in statistics?

Answer 27

1. Arises empirically- many statistical techniques for analysing normal distributed data are ROBUST and not affected by modest departures from normality
2. Some VARIABLES are normally distributed because the BIOLOGICAL MECHANISM CONTROLING THEM such as variable polygenic control
3. DEPARTURE FROM NORMALITY DECREASES AS THE SAMPLE SIZE INCREASES- If the population is very skew the effect is noticeable even in samples as small as 10