SPSS Normality with Kolmogorov Smirnov and Shapiro Wilk tests

spss to determine if variable contiguous variable is normal or not we're going to go ahead and use the kolmogorov smirnoff and the shapiro's wilk test so it goes fast let's watch we're going to go to analyze descriptive statistics explore we'll kick all three of them in there we're going to go to plots don't use stem and leaf normally do the histogram even though it can be misleading but here's the main one normality plots with tests okay that's going to bring up the kolmogorov and the shapiro wilk click click click and there's our first box there's the descriptives and here's the coma gurudos schmoon off these first columns right one two three these are the ks tests schmur enough test and then the next three one two three the shapiro will normally they agree okay normally they agree they don't always agree so researchers tend to say if you got big sample size and they're not real specific on how big but normally 2000 or above the komagorov smirnoff is more accurate and if you got small sample size again it's kind of gray area which was considered small the shapiro wilk is more accurate so shapiro will normally found one book that said you know 20 or less for the shapiro wilk anything over 20 should use the coal magor offshore enough but again like said they usually agree the coleman girl screwing up test it has little special thing some of these things will you'll have little asterisk and the significance will be two zero zero what that means is that the software is calculating that if you had bigger sample size then the data set would probably be normal that's what that means okay but these are all less than 0.05 which means that anxiety variable violated the assumption of normality as did depression and stress in other words none of these are normal remember when you're checking assumptions if the if the p-value is less than 0.05 in other words if you get significance while checking an assumption that means you violated that assumption i'll say that again students get confused on this lot so think about the null hypothesis when checking assumptions right the word no or not is in the null hypothesis so the null hypothesis would be these variables did not violate the assumption of normality that's the null they did not violate okay so you get to reject that right because the p-value is less than 0.5 you reject the null therefore the null becomes the alternative which is true the the variables did violate the assumption and again this is why you don't go by the histograms that one doesn't look too bad to me but it's not normal right and this one looks pretty normal but according to the the kolmogorov schmornoff and the shapiro none of these are normal right so there is depression again it looks pretty normal to me but not to the math that's what we got to go by now this one does look skewed okay okay but that's it and again this is your box right here so remember if it vile if if the significance is less than .05 it had violated the assumption and that's true for all assumptions not just normality last time if the p-value is less than 0.05 when checking assumptions that means you violated that assumption all right that's enough mgz you