Practical Statistics - PowerPoint PPT Presentation

Practical statistics
Download
1 / 29

  • 303 Views
  • Updated On :
  • Presentation posted in: Pets / Animals

Practical Statistics. Chi-Square Statistics. There are six statistics that will answer 90% of all questions! Descriptive Chi-square Z-tests Comparison of Means Correlation Regression. Chi-square: Chi-square is a simple test for counts….. . Chi-square:

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha

Download Presentationdownload

Practical Statistics

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Practical statistics l.jpg

Practical Statistics

Chi-Square Statistics


Slide2 l.jpg

  • There are six statistics that will

  • answer90% of all questions!

  • Descriptive

  • Chi-square

  • Z-tests

  • Comparison of Means

  • Correlation

  • Regression


Slide3 l.jpg

Chi-square:

Chi-square is a simple test for counts…..


Slide4 l.jpg

Chi-square:

Chi-square is a simple test for counts…..

Which means: nominal data

and… if some cases…

Ordinal data


Slide5 l.jpg

  • Chi-square:

  • There are three types:

  • Test for population variance

  • Test of “goodness-of-fit”

  • Contingency table analysis


Slide6 l.jpg

  • Chi-square:

  • There are three types:

  • Test for population variance


Slide7 l.jpg

  • Chi-square:

  • There are three types:

  • Test for population variance

  • Test of “goodness-of-fit”

Where o = frequency of actual observation, and

e = frequency you expected to find


Slide8 l.jpg

According to marketing research, the clientele

of a Monkey Shine Restaurant is made up of 30%

Western businessmen, 30% women who

stop in while shopping, 30% Chinese business men,

and 10% tourists. A random sample of 600 customers

at the Kowloon Monkey Shine found 150 Western

businessmen, 190 Chinese businessmen, 100 tourists,

and 65 women who were shopping.

Is the clientele at this establishment different

than the norm of the this company?


Slide10 l.jpg

= 5.00 + 0.56 + 2.22 + 26.67 = 34.45

With (4-1) degrees of freedom


Slide11 l.jpg

The chi-square distribution is highly skewed

and dependent upon how many degrees of

freedom (df) a problems has.


Slide12 l.jpg

The chi-square for the restaurant problem was:

Chi-square = 34.45, df = 3

By looking in a table, the critical value of

Chi-square with df = 3 is 7.82. The probability

that the researched frequency equals the

frequency found in the MR project was p < .001.

http://www.fourmilab.ch/rpkp/experiments/analysis/chiCalc.html


Slide13 l.jpg

By looking at the analysis, it is obvious that

the largest contribution to chi-square came from

the tourists.

= 5.00 + 0.56 + 2.22 + 26.67 = 34.45 df = 3

Hence, the Kowloon property is attracting more

tourist than what would be expected at the Monkey

Shine.


Slide14 l.jpg

  • Chi-square:

  • There are three types:

  • Test for population variance

  • Test of “goodness-of-fit”

  • Contingency table analysis

Where o = frequency of actual observation, and

e = frequency you expected to find


Slide15 l.jpg

A contingency table

is a table with numbers grouped by frequency.


Slide16 l.jpg

A contingency table

is a table with numbers grouped by frequency.

There are three groups: brand loyal customers,

regular buyers, and occasional buyers.

Each is asked if they like the taste of new

product over the old. They answer with a “yes”

or a “no.”


Slide17 l.jpg

A contingency table would look like this:


Slide18 l.jpg

A contingency table

is a table with numbers grouped by frequency.

All the numbers in the table are “observed”

frequencies (o).

So, what are the expected values?


Slide19 l.jpg

The expected values (e) would be a random

distribution of frequencies.


Slide20 l.jpg

The expected values(e) would be a random

distribution of frequencies. These can be calculated

by multiplying the row frequency by the column

frequency and dividing by the total number of

observations.


Slide21 l.jpg

For example, the expected values (e) of “loyal”

And “yes” would be (150 X 90)/270 = 50


Slide22 l.jpg

For example, the expected values (e) of “regular”

And “no” would be (120 X 100)/270 = 44.4


Slide23 l.jpg

The expected values (e) for the entire table

would be:


Slide24 l.jpg

The chi-square value is calculated for every cell,

and then summed over all the cells.


Slide25 l.jpg

The chi-square value is calculated for every cell:

For Cell A: (50-50)^2/50 = 0

For Cell D: (40-44.4)^/44.4 = 0.44


Slide26 l.jpg

The chi-square value is calculated for every cell:


Slide27 l.jpg

The chi-square value is calculated for every cell:

Chi-square = 0 + 0 + .35 + .44 + .44 + .54 = 1.77

The df = (r-1)(c-1) = 1 X 2 = 2


Slide28 l.jpg

A chi-square with a df = 2 has a critical value

of 5.99, this chi-square = 1.77, so the results

are nonsignificant.

http://www.fourmilab.ch/rpkp/experiments/analysis/chiCalc.html

The probability = 0.4127.

This means that the distribution is random, and

there is no association between customer type

And taste preference.


Slide29 l.jpg

A chi-square with a df = 2 has a critical value

of 5.99, this chi-square = 1.77, so the results

are nonsignificant.

This means that the distribution is random, and

there is no association between customer type

And taste preference.

Note: This type of chi-square is a test of

association using nothing but

counts (frequency);

VERY useful in business research.


ad
  • Login