# data[].attributes.body
I am always confused when reading the text of the questions when it is referring to the mean scores of variables M that we calculate by doing descriptive statistics

AND

The mean scores of variables that we calculate Z  values and then the mean using the Z values. which is the mean of many questions that are measuring the same thing.

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I do not understand this what you mean with this sentence. Do you mean the way that is written in the slides? or are there certain standards we should know about. Because I think not everything is written in the slides, I mean there are things that we may need to report that are not specified in the slides.

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Cross tabulation table in Chi-square test of independence

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Cross tabulation table in Chi-square test of independence

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I am confused if the numbers and percentage in this table

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I am very confused about variable types. Sometimes a variable is continuous but in other times it is considered categorical. This makes me cannot decide the right test.

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categorical variables cannot be normally distributed. Is this right? 

# data[].attributes.subject
categorical variables cannot be normally distributed. Is this right? 

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So like gender variable, it only contain to values either male or female so it could not be normally distributed?

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I don't understand why we have to reverse negatively worded items?

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Before we run a T Test or an ANOVA  test, we need to test the normality. Do we have to test the normality of only the dependent variable or also the independent one?
2. Do we have to calculate the descriptive statistics (mean, median, SD...) every time and illustrate the main values in the table?

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When we report in the results that the data is normally distributed or not, can we report it only by illustrating the skewness and kurtosis or it is better to say that the Kolmogorov and shapiro-wilk show that it is normally distribution?

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1. For the final assignment, if we test the normality and the data is not normally distributed. Do you expect us to delete the outliers to try to use a parametric test or not?

2. The instructions say that we have to illustrate the interpretations/conclusions, what do you mean by this? Is it an extra paragraph apart from the results' text?

3. In the first exercise, do we have to create a chart with excel and calculate the frequency distributions?

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if for the same variable, the P value of kolmogorov and Shapiro are different, so one of them is less than 0.05 and the other is more than 0.05. What should we consider our data: normal or non normal?

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this tests: A comparison of the two groups’ averages (mean)

So if a question says:

Is there a difference between men and women in the X variable?

We Must calculate the mean of this X variable first then do the T-test? Even if it is not explicitly said in the question that we do the mean of X ?

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mean scores of the literacy sum score

OR just

the literacy sum score

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If we make the ANOVA test and the result is that H0 is accepted-->there is no difference...

When reporting: should we put the table or we just report by text?

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When we run a chi-square test, do we illustrate the results in a text or also in a table?

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When reporting N in the APA style tables: do we mention the N with or without the missing values. So if we have overall 100 entry of 100 participants but in Variable X there were 10 missing values. So should we report the N=100 or 90?