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# Inferential statistics - PowerPoint PPT Presentation

Inferential statistics. Why statistics are important. Statistics are concerned with difference – how much does one feature of an environment differ from another Magnitude : The comparative strength of two variables.

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## PowerPoint Slideshow about ' Inferential statistics ' - ermin

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Presentation Transcript

• Statistics are concerned with difference – how much does one feature of an environment differ from another

• Magnitude: The comparative strength of two variables.

• Reliability. The degree to which the measure of the magnitude of a variable can be replicated with other samples drawn from the same population.

• Relationships – how does much one feature of the environment change as another measure changes

Correlation or regression

r=0.73

N=20

p<0.01

Mean (M or X), is the sum (SX) of all the sample values ((X1 + X2 +X3.…… X22) divided by the sample size (N).

SX = 45, N = 22. M = SX/N = 45/22 = 2.05

• median is the "middle" value of the sample. There are as many sample values above the sample median as below it.

• If the sample size is odd (say, 2a + 1), then the median is the (a+1)st largest data value. If the sample size is even (say, 2a), then the median is defined as the average of the ath and (a+1)st largest data values.

• The mode is the single most frequently occurring data value.

• The midrange is the midpoint of the sample -- the average of the smallest and largest data values in the sample.

• Find the Mean, Median and Mode

All normal distributions have similar properties. The percentage of the scores that is between one standard deviation (s) below the mean and one standard deviation above is always 68.26%

Mean =77.48 SD=7.15

N=62

-2SD -1SD 0 +1SD +2SD

-14.30 -7.15 0 +7.15 +14.30

Is there a difference between Rich and poor scores percentage of the scores that is between one standard deviation (s) below the mean and one standard deviation above is always 68.26%

Is there a significant difference between Polynesian and “other” scores

Mean =81.9 SD=6.5

N=20

Mean =75.0 SD=6.8

N=20

• the difference in mean scores of two or more events

- the bigger the gap between means the greater the difference

• the degree of variability in the data

- the less variability the better

Variance and Standard Deviation different

These are estimates of the spread of data. They are calculated by measuring the distance between each data point and the mean

variance (s2) is the average of the squared deviations of each sample value from the mean = s2 = S(X-M)2/(N-1)

The standard deviation (s) is the square root of the variance.

• The extent to which the sample is representative of the population from which it is drawn

- the bigger the sample the greater the likelihood that it represents the population from which it is drawn

- small samples have unstable means. Big samples have stable means.

Estimating difference different

The measure of stability of the mean is the Standard Error of the Mean = standard deviation/the square root of the number in the sample.

So stability of mean is determined by the variability in the sample (this can be affected by the consistency of measurement) and the size of the sample.

The standard error of the mean (SEM) is the standard deviation of the normal distribution of the mean if we were to measure it again and again

Yes it’s significant. The Standard Errors of the Mean = 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

Is the difference between means 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals significant?

What is clear is that the mean of the Rich group is well outside of the area where there is a 95% chance that the mean for the Poor Group will fall, so it is likely that the Rich mean comes from a different population than the Poor mean.

The convention is to say that if mean 2 falls outside of the area (the confidence interval) where 95% of mean 1 scores is estimated to be, then mean 2 is significantly different from mean 1. We say the probability of mean 1 and mean 2 being the same is less than 0.05 (p<0.05) and the difference is significant

p

The significance of 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervalssignificance

• Not an opinion

• A sign that very specific criteria have been met

• A standardised way of saying that there is a

There is a difference between two groups – p<0.05;

There is no difference between two groups – p>0.05;

There is a predictable relationship between two groups – p<0.05; or

There is no predictable relationship between two groups - p>0.05.

• A way of getting around the problem of variability

95% of M1 distri-bution 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

2.5% of M1 distri=bution

2.5% of M1 distri-bution

If you argue for a one tailed test – saying the difference can only be in one direction, then you can add 2.5% error from side where no data is expected to the side where it is

1-tailed test

2-tailed test

T-test results 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

Tests of significance 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

• Tests of difference – t-tests, analysis of variance, chi-square, odds ratios

• Tests of relationship – correlation, regression analysis

• Tests of difference and relationship – analysis of covariance, multiple regression analysis.

Chi-squared ( 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervalsc2) comparison of age in the sample vs the Waitakere population

Values of chi-square for the research project 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

The fact that two groups are not significant means that there is no significant difference between the sample and Waitakere population except for culture and qualifications

r = 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals(S(X – MX)*((Y – MY))/(N*SX*SY)

r =correlation coefficient

X = Height

Y= Self Esteem

MX=Mean of X

MY =Mean of Y

SX=Standard deviation of X

SY=Standard deviation of y

r=0.73 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

N=20

Level of Significance 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

One or two tails? 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

What degrees of freedom

What level of significance should be chosen?

Correlations 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

The perfect positive correlation 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

The perfect negative correlation 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

No correlation at all 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

A perfect relationship, but not a correlation 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

How correlation is used and misused 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals

Normality of residuals, Linearity, & Homoscedasticity 1.45 and 1.53, so the 95% confidence interval will be about 3 points (1.96*1.5) either side of the mean. The means falls outside each other’s confidence intervals