Hello everyone, I am facing some problems concerning my data normality of my dependent variable, my results are contradicted and I couldn't make my conclusion. Which criteria should I based for to say if the data is normally distributed or not ?
Thank you in advance
Hello there!
could you help me to show or explain how to run this formula in Spss step by step? Thank you in advance.
My background of Statistic is not good :(
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Munificence to be obtained by:
a. Regressing time against sales of industry over the previous 10 years
of period and;
b.Taking the ratio of the regression slope coefficient to the mean value of sales over the same period.
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Can you help me with stats and probability.
State whether the following are true or false and give a brief explanation. Explain true/false answer
i. Skewness of a distribution cannot be determined from a boxplot.
ii. For any event A, it is possible for P(A) + P(Ac
) < 1, where Ac denotes
the complement set.
iii. A standardised normal random variable has a standard deviation equal to
I run binary model: one category has 112 sample size and other has only 28, does it create problem due to vast difference in sample size between categories?
Pls I need help so to this
Question:
A) Searching for optimality in a rapidly changing world is like chasing a shadow the optimum changes as our perception changes.
B) The Operational Research Society's definition of Operational Research does not mention optimization yet most Operational Research technique assumes it
*Required:*
Comment on the above statements giving examples why it might. Not be appropriate to seek
Hello. I'm fairly new on this platform and would appreciate it if I could be assisted. I have read somewhere that for a 7 point Likert scale questionnaire, 4 is the Test value, I hope I got that one right. So my question is, how do I determine Test value for a point Likert scale?
Again how do I differentiate between Test value and t-test? I find them confusing
Hi. need help. I am new to research data analysis and the last time I came across it was when I was still in Uni. To cut the story short, wanted some advise on the research analysis that I am doing. We wanted to know what scores from candidate's pre-employment data can predict a high scores in Training outcome (probability of candidate to excel or to be dismissed from training). Which statistical analysis can we use?
Hallo Dason,
I have a question in Conditional Probability and I would appreciate if you could help me solve it.
I have the probability of of the Hourly temperature of the day. if my temperature varies from -3,-2,-1,0.....+9 and I know the probability for each temp. every hour through the day (for example that probability that the temp is +1°C at 12:00 am is 13% and at 01:00 am is 15% and so on for 24 hours.
Is this a right description? I found it in a book but I am confused:
"Three main statistical methods are used in the data analysis: descriptive statistics, inferential statistics, and regressions analysis." and
"Inferential statistics tests the relationship between two data sets or two samples, and a hypothesis is usually set for the statistical relationships
between them."
yes exactly, I want random data like hemogloblin, kolesterol and weight, and lets say I have 20 deaths in 100 patient as binary outcome, I want to have random data ( each within specified limits , hemoglobln values should be between 9-16 for example ) that will give me the specified odds ratio after multivariate regression analysis
3 variables , each has prespecified odds ratio which are significant and in a predetermined confidence interval
for example after multivariate logistic regression analysis I find A variables odds 1.4 (1.1-16) , B variables 1.6 ( 1.23-1.40) and C variable 2.3 ( 1.4-3.3)
now I want 120 A,B, C variables with a prespecified mean, SD, how can I produce this data
3 variables , each has prespecified odds ratio which are significant and in a predetermined confidence interval
for example after multivariate logistic regression analysis I find A variables odds 1.4 (1.1-16) , B variables 1.6 ( 1.23-1.40) and C variable 2.3 ( 1.4-3.3)
now I want 120 A,B, C variables with a prespecified mean, SD, how can I produce this data
3 variables , each has prespecified odds ratio which are significant and in a predetermined confidence interval
for example after multivariate logistic regression analysis I find A variables odds 1.4 (1.1-16) , B variables 1.6 ( 1.23-1.40) and C variable 2.3 ( 1.4-3.3)
now I want 120 A,B, C variables with a prespecified mean, SD, how can I produce this data
3 variables , each has prespecified odds ratio which are significant and in a predetermined confidence interval
for example after multivariate logistic regression analysis I find A variables odds 1.4 (1.1-16) , B variables 1.6 ( 1.23-1.40) and C variable 2.3 ( 1.4-3.3)
now I want 120 A,B, C variables with a prespecified mean, SD, how can I produce this data
Currrntly I'm doing masters thesis on migration using count model.poisson and neg.binomial have no problem but when i try zeroinflated and hurdle model some pridctor variable shows error in r software.....like computationally singular
as.matrix.fit$hessian...
So how I can fix the problem and include the variable in analysis???
a) the same for two successive hours?
b) Increase by +1 degree in the next hour
c) decrease by -1 degree in the next hour