Nymos
2 years & 2 months ago

For the research of my two variables, I’ve done the independent t-test, one way anova and correlations. the Mean difference is significant at 0.05 level( in post hoc)

for correlations, it is significant at 0.01 (2tailed) My r-value is 0.446 and the p- value is <0.001 for the correlation of the two variables. So, it should be rejected???

Riya Jain
2 years & 1 month ago

Hi Nymos,
Yeah the variable has to be excluded from the model because the pearson correlation value you mentioned is 0.446. Though the significance is 0.01 < 0.05 but having low correlation you can't consider it for impact analysis.

Reply

Manic
2 years & 7 months ago

I’m getting <.001 for my chi square p value what does it mean? why the Greater sign is appearing?

Riya Jain
2 years & 7 months ago

Hi Manic
The p-value of <0.001 means that your analysis significance level is close to 0, depicting that null hypothesis of no relationship between the variables would be rejected.

Reply

Juliana
2 years & 8 months ago

Hello,
I’d like some help understanding correlation coefficients and sig 2-tailed. Can you help?
Thank you kindly!

Riya Jain
2 years & 7 months ago

Hi Juliana,
The correlation coefficient explains the magnitude of linkage between variables whiles its significance value explains whether that variable is relevant or not.
For more details on interpretation, you can refer to this article: Understanding correlation regression
and How to interpret results from the correlation test?

Reply

OKPARA JESSE
3 years & 5 days ago

i am presently doing my Msc in In human Resoursr mgt. but i am finding it difficult to collate result for my chapter 4 which is ANALYSES AND INTERPRETATIONS OF DATA.
i dont kmow how to get the correlation coeficient of more than 2 variables and my chi-square result.
please i need your help Mrs. Priya Chetty…..plsssssss

Jayasudhajeyabalan
3 years & 1 week ago

AVGRBEFF AVGSPTFF AVGPAFF vs HMF AVGFFCH
Reason behind eating fast food
Pearson Correlation 1 .284** .401** .164*
Sig. (2-tailed) .000 .000 .019
N 203 203 203 203
Students’ preference on types of Fast food
Pearson Correlation .284** 1 .239** .161*
Sig. (2-tailed) .000 .001 .022
N 203 203 203 203
Perception about fast food Vs Homemade food
Pearson Correlation .401** .239** 1 .101
Sig. (2-tailed) .000 .001 .152
N 203 203 203 203
fast food consumption habits Pearson Correlation .164* .161* .101 1
Sig. (2-tailed) .019 .022 .152
N 203 203 203 203

Sileshi
4 years & 2 weeks ago

Thank you

Shahid raza
4 years & 3 months ago

Respected sir i havent interpret these belo tables its a humble request for you to plkease help me to interpret it
KMO and Bartlett’s Testa
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .530
Bartlett’s Test of Sphericity Approx. Chi-Square 273.492
Df 120
Sig. .000

Variance table
No of components Total Variance
1 3.088 15.707
2 2.437 12.398
3 2.136 10.864
4 1.825 9.285
5 1.688 8.586
6 1.461 7.434

Factor Loads
Elements Loads
Family income effect student academic performance positively .852
Peaceful home environment positively affect student outcomes .827
Educated and cooperative parents positively influence student performance .481
Drinking water source 1.484
Joint family structure effect student performance negatively 1.239
Working of mother negatively affects the student outcomes 1.316
If you have any other home also, is it rented or not 1.686
Any other achievement in non -education 1.249

Riya Jain
4 years & 2 months ago

Hey
KMO and Bartlett’s Testa interpretation
Kaiser-Meyer-Olkin Measure of Sampling Adequacy value is 0.530 which is greater than the required value of 0.5, thus the factor analysis for representing the proportion of variance in the variable is useful.
The significance value of Bartlett’s Test of Sphericity test is less than the significance value of the study i.e. 0.000 < 0.05, thus the null hypothesis that the correlation matrix is identity matrix is rejected and hence the dataset is suitable for factor analysis.
Variance table interpretations
Variance tables show that 1st-factor having a variance of 3.088 accounts for 15.707% of the total variance, 2nd-factor variance of 2.437 consists of 12.398% of the total variance, 3rd-factor variance of 2.136 accounts for 10.864% of total variance, 4th-factor variance of 1.825 is 9.285% of total variance, 5th-factor variance of 1.688 depicts 8.586% of total variance, and last factor variance i.e. 1.461 shows 7.434% of total variance.
Factor Loading interpretation
As the factors Drinking water source; Joint family structure effect student performance negatively; Working of mother negatively affects the student outcomes; If you have any other home also, is it rented or not; and Any other achievement in non -education; has highest factor loading i.e. greater than 1 thus, these would be the factors considered for further analysis.

Reply