Download presentation

Presentation is loading. Please wait.

Published byBreanna Dubois Modified over 2 years ago

1
Using SPSS

2
Handy buttons Switch between values & value labels Info about variables (& ‘Go To’)

3
Handy buttons Click with the right mouse button on a variable you want to know more about… In dialog boxes you always have help nearbye…

4
Handy buttons … and you will get variable info…

5
SPSS output viewer Just let’s make a table with some corre- lations

6
SPSS output viewer Now, click with the right mouse button on table en choose Open…

7
SPSS output viewer … and you will get a new window wherein you can edit the table

8
SPSS output viewer Now, let’s look at the Pivoting Trays

9
SPSS output viewer The pivots of the table… This pivot represents the statistics This pivot represents the variables

10
SPSS output viewer Now put the pivot of the statistics in the layer (‘capa’) and the form of the table will change!

11
SPSS Syntax In each dialogbox you will see a button Paste (‘Pegar’) to create syntax.

12
SPSS Syntax After having done Paste (‘Pegar’) you will see a ‘command’ in the syntax window.

13
SPSS Syntax You can as well open a specific syntax file, i.e. Ridge Regression (in the SPSS program folder)

14
SPSS Syntax Why would you use syntax??? To do analyses repeatedly To use all the functions of SPSS (in dialogboxes +/- 95% is incorporated) To be independent of dialogboxes, that keep changing…(and syntax never changes)

15
SPSS Options Make your SPSS life easy with Edit | Options For instance by using the session journal file as a syntax file…

16
Regression & Logistic Regression Revisited

17
Graphing relationships Transforming variables Missing Values Outliers & Influential Points Categorical predictors Regression revisited; topics:

18
Graphing Relationships Matrixplot to make a plot of a lot of variables

19
Specify variables Graphing Relationships

20
Result in output window Graphing Relationships

21
You can edit the Graph like you edited a table by opening the graph (click with right mouse button on the graph and choose Open) Graphing Relationships

22
Now choose Chart | Options

23
Graphing Relationships Then ask for a fit line

24
Graphing Relationships Some remarks: -GDP is related in a non linear way with other variables - variable Aids Cases we have a very influential point (not an outlier, but influential!) - correlation between female life expectation and male life expectation is almost 1

25
Graphing Relationships Let’s try to transform gdp_cap in order to get linear relationships with other variables. First let’s look at the distribution of gdp_cap with a histogram: We need to bring values on the right closer to values on the left. We might try a LN transformati on…

26
Transforming variables

27
The histogram of transformed variable is:

28
Transforming variables Relationships are nicely linear !

29
Transforming variables Note: you probably want to make a variable lifeexp out of life expectancy males and life expectancy females: Tip: use function Mean in stead of using the ‘+’ and dividing by 2

30
Categorical Predictors Is income dependent on years of age and religion ?

31
Categorical Predictors Compute dummy variable for each category, except last

32
Categorical Predictors And so on…

33
Categorical Predictors Block 1

34
Categorical Predictors Block 2

35
Categorical Predictors Ask for R 2 change

36
Categorical Predictors Look at R Square change for importance of categorical variable

37
Categorical Predictors Zodiac is actually a categori cal variable

38
Categorical Predictors Indicator coding scheme

39
Categorical Predictors

40
Annotated output of regression analysis (it uses the file data/elemapi.sav ) http://www.ats.ucla.edu/stat/spss/webbooks/reg/chapter1/annotated1.htm For more on regression, see: http://www.ats.ucla.edu/stat/spss/webbooks/reg/chapter1/spssreg1.htm

41
Categorical Predictors

42
Outliers

44
Saving residuals

45
Influential Points

47
Saving distances and influence measures as variables

48
Multicollinearity Diagnostics

49
Multicollinearity

Similar presentations

OK

Week 5: Logistic regression analysis Overview Questions from last week What is logistic regression analysis? The mathematical model Interpreting the β.

Week 5: Logistic regression analysis Overview Questions from last week What is logistic regression analysis? The mathematical model Interpreting the β.

© 2018 SlidePlayer.com Inc.

All rights reserved.

Ads by Google

Free download ppt on obesity Ppt on mbti personality test Ppt on remote controlled fan regulator Ppt on democracy class 9 Ppt on e commerce Ppt on natural numbers symbol Ppt on digital media broadcasting projects Figurative language for kids ppt on batteries Ppt on energy cogeneration definition Ppt on peace and nonviolence