regresi 2

Katakanlah kita ingin mengetahui kaitan antaran jualan(IV) dan keuntungan(DV).
Contoh:
Data yang diperolehi dari satu laporan menunjukkan jualan (dalam ribu RM) dan keuntugan (dalam ribu RM)bagi sepuluh buat syarikat seperti berikut:

syarikat	jualan	keuntungan
A	35	42
B	21	35
C	33	51
D	11	20
E	57	69
F	28	37
G	61	68
H	15	21
I	75	86
J	47	52

data diatas kalau digambarkan dalam graph akan jadi seperti berikut:

(Graf ini dibuat menggunakan MS EXCEL)

Untuk membuat analisis regresi untuk membuat telahan (projection) tentang keuntungan menggunakan SPSS, mari masukkan data kedalam SPSS.

(Andaian anda sudah pun mempunyai package software SPSS dalam komputer anda. Disini saya menggunakan IBM SPSS Statistics 19) 

Reliability Test - Cronbach Alpha

What is reliability Analysis in Statistics
Reliability analysis allows you to study the properties of measurement scales and the items that compose the scales. The Reliability Analysis procedure calculates a number of commonly used measures of scale reliability and also provides information about the relationships between individual items in the scale. Intraclass correlation coefficients can be used to compute inter-rater reliability estimates.

There are a few reliability test, and the most commonly used in social science is the Cronbach Alpha test.

What does Cronbach's alpha mean? 
Cronbach's alpha is a measure of internal consistency, that is, how closely related a set of items are as a group.  A "high" value of alpha is often used (along with substantive arguments and possibly other statistical measures) as evidence that the items measure an underlying (or latent) construct. However, a high alpha does not imply that the measure is unidimensional. If, in addition to measuring internal consistency, you wish to provide evidence that the scale in question is unidimensional, additional analyses can be performed. Exploratory factor analysis is one method of checking dimensionality. Technically speaking, Cronbach's alpha is not a statistical test - it is a coefficient of reliability (or consistency). 

Cronbach's alpha can be written as a function of the number of test items and the average inter-correlation among the items.  For conceptual purposes, the formula for the standardized Cronbach's alpha:

wHere N  is equal to the number of items, c-bar is the average inter-item covariance among the items and v-bar equals the average variance. 

If  the number of items is increased, Cronbach's alpha will also increase.  Additionally, if the average inter-item correlation is low, alpha will be low.  As the average inter-item correlation increases, Cronbach's alpha increases as well (holding the number of items constant).

To get the Cronbach Alpha value in SPSS, from the QOL questions, let us ru some reliability test. 

1. Open the QOL dataset.
2. Assuming the dataset is opened, 

click => Analyse

              =>Scale

                   => Reliability Analysis

3.   In the reliability Analysis window, bring F4.1, F4.2 and F4.3 into the items box.You can do this by drag-and-dropping the variables into their respective boxes or by using the  button. 

4.   Leave the Model: set as "Alpha", which represents Cronbach's alpha in SPSS. If you want to provide a name for the scale, enter it in the Scale label: box. 

5.    Click => Statistics..and the Reliability Analysis : Statistics box appears.

6.    Click,=>" Item" and "Scale if item deleted" and also "Correlations".

7.    Click the  button. This will return you to the Reliability Analysis dialogue box.

8.    Click the  button to generate the output.

6.   The output will appear as follows:

• SPSS produces many different tables. The first important table is the Reliability Statistics table that provides the actual value for Cronbach's alpha, 
• Cronbach Alpha score for this variable with three items considered is 0.937,which indicates a high level of internal consistency for our scale with this specific sample.
• The Item-Total Statistics table presents the "Cronbach's Alpha if Item Deleted" in the final column, 
• This column presents the value that Cronbach's alpha would be if that particular item was deleted from the scale. We can see that removal of any question, would result in a lower Cronbach's alpha. Therefore, we would not want to remove these questions. 
• If Removal of any question would lead to a small improvement in Cronbach's alpha, and we can also see that the "Corrected Item-Total Correlation" value will also be low for the item. This might lead us to consider whether we should remove this item.

• Cronbach's alpha simply provides you with an overall reliability coefficient for a set of variables (e.g., questions). If your questions reflect different underlying personal qualities (or other dimensions), for example, employee motivation and employee commitment, Cronbach's alpha will not be able to distinguish between these. In order to do this and then check their reliability (using Cronbach's alpha), you will first need to run a test such as a principal components analysis (PCA).

Checking Frequencies

Now let us start by running the frequencies.
One of the purpose of running the frequencies is to check whether what we had done is right or wrong before we can proceed with our analysis.
Click according to the following pictures:

choose G1.3 to check for the frequency.

your output will look like the following. 

•If you don’t mind going back and forth referring to the questionnaire each time you run your analysis, then it is okay, with your variables.

•If you want the output give you immediate understanding of your data, then more information got to be done with your variable.

Now back to the variable view and start doing some editing.

Click variable view on the bottom left of your data file, and edit variable G1.3.

Do the same to others by referring to the Questionnaire.

Click the cell, under the column value for G1.3 and key in as shown in the following..

next run again "Analyze->descriptive--> frequency"

choose G1.3, and click OK. see the difference in the output.

Then you can proceed with other variables too,

Creating a Datafile in SPSS

Before you can proceed with running your analysis using SPSS, you should have and open a datafile.
For the beginning copy and paste the "Example Data file from the earlier post and paste into a SPSS data file.
After you had done that, it should look something like this.

Edit the variables where necessary by clicking the "variable view" at the bottom left of the data file.

After clicking the variable view, you should see something like this in the variable view.

If everything is okay now you are ready to proceed with the next step.

Example data file

Example data file for short course on SPSS

siri	F1.1	F1.2	F1.3	F2.1	F2.2	F3.1	F3.2	F4.1	F4.2	F4.3	G1.1	G1.2	G1.3	G1.4	G1.5	G1.6
001	4	4	4	4	3	3	2	1	2	2	1	2	2	2	1	3R
002	5	5	4	3	3	2	3	2	1	1	1	2	1	2	1	3R
003	3	4	3	3	3	2	3	2	4	3	2	3	2	2	2	-
004	1	1	2	2	2	1	1	4	4	4	2	3	1	4	2	-
005	2	1	1	2	1	1	1	4	4	4	4	3	2	4	2	-
006	3	2	1	3	1	1	2	3	4	3	1	4	2	4	2	-
007	4	3	3	2	2	2	2	3	3	3	1	4	1	2	2	-
008	5	3	3	3	3	2	2	1	3	2	2	4	3	1	2	-
009	1	2	1	1	2	1	2	5	5	4	3	3	3	4	2	-
010	1	3	1	2	2	1	1	5	5	5	1	3	4	3	2	-
011	2	3	2	2	3	2	2	3	5	4	1	3	1	3	2	-
012	2	1	2	2	2	1	2	4	4	5	2	1	1	5	2	-
013	3	4	3	3	3	2	3	3	4	3	1	1	1	4	2	-
014	4	2	2	3	2	2	3	3	4	4	1	2	1	3	2	-
015	1	2	1	1	1	1	1	5	5	5	2	2	2	5	2	-
016	1	1	1	2	1	1	1	5	5	5	2	3	2	5	2	-
017	2	1	3	1	1	2	2	5	5	5	2	3	2	4	22	-
018	1	1	1	1	1	1	2	5	5	5	2	4	2	5	2	-
019	2	2	2	3	2	2	3	3	3	4	1	4	2	4	2	-
020	3	3	3	4	3	2	3	3	3	3	1	1	2	3	2	-

QOL questionnaire

Let us start with the sample questionnaire first. This is just a sample questionnaire to be use for the course.
 Rupa Q yang sebenar:

Actual look of the sample Questionnaire. But it is too small and not readible. So the Qare copied into this blog. The questions are as follows:

Serial No :

Instructions

This questionnaire asks how you feel about your quality of life, health, and other areas of your life.

Please answer all the questions. If you are unsure about which response to give to a question, please choose the one that appears most appropriate. This can often be your first response.  Please keep in mind your standards, hopes, pleasures and concerns. We ask that you think about  your life in the last two weeks.

For example, thinking about the last two weeks, a question might ask:

		Not at all	A little	A moderate amount	Very Much	An extreme amount
1	How much do you worry about your health?	1	2	3	4	5

You should circle the number that best fits how much you have worried about your health over the last two weeks. So you would circle the number 4 if you worried about your health “Very much”, or circle number 1 if you have worried “Not at all” about your health. Please read each question,  assess your feelings, and circle the number on the scale for each question that gives the best answer  for you.

 Thank you for your help

	The following questions ask about how much you have experienced certain things in the last two weeks, for example, positive feelings such as happiness or contentment. If you have experienced these things an extreme amount circle the number next to “An extreme amount”. If you have not experienced these things at all, circle the number next to “Not at all”. You should circle one of the numbers in between if you wish to indicate your answer lies somewhere between “Not at all” and “Extremely”. Questions refer to the last two weeks.
		Not at all	A little	A moderate amount	Very Much	An extreme amount
F1.1	Do you worry about your pain or discomfort	1	2	3	4	5
F1.2	How difficult is it for you to handle any pain or discomfort?	1	2	3	4	5
F1.3	To what extent do you feel that (physical) pain prevents you from doing what you need to do?	1	2	3	4	5
F2.1	How easily do you get tired?	1	2	3	4	5
F2.2	How much are you bothered by fatigue?	1	2	3	4	5
F3.1	Do you have any difficulties with sleeping?	1	2	3	4	5
F3.2	How much do sleep problems worry you	1	2	3	4	5
F4.1	How much do you enjoy life?	1	2	3	4	5
F4.2	How positive do you feel about the future?	1	2	3	4	5
F4.3	How much do you experience positive feelings in your life?	1	2	3	4	5

G1	About You
1.	Gender	1 2	Male Female	1
2	Highest education received	1 2 3 4	Primary School Secondary School University Post-Graduate	2
3	What is your marital status?	1 2 3 4	Single Married Separated /Divorced Widowed	3
4	How is your health?	1 2 3 4 5	Very poor Poor Neither poor nor good Good Very  Good	4
5	Are you currently ill?	1 2	Yes…….. (go to Q6) No ………(end)	5
6	If yes, what is your diagnosis		________________

Thank You.