

 Calculating basic statistical

Step one:

Calculate Frequencies on the Split Groups
 √ Data
 * Split File
Your screen will show that all cases are going to be analyzed and a “do not create groups”. You will need to click the compare groups and move the independent variable over to the “Group Based on”.
After you do this, your screen should resemble the following:

Then click OK
 √ Analyze
 * Descriptive Statistics
 * Frequencies
 √ Move over the dependent (outcome) variable
 √ Statistics
 * Mean
 * Standard Deviation
 * Skewness [Note. Skewness refers to the extent to which the data are normally distributed around the mean. Skewed data involve having either mostly high scores with a few low ones or having mostly low scores with a few high ones.] Readers are referred to the following sources for a more detailed definition of skewness:

(External Link)&term_id=356

(External Link)
 To standardize the skewness value so that its value can be constant across datasets and across studies, the following calculation must be made: Take the skewness value from the SPSS output and divide it by the Std. error of skewness. If the resulting calculation is within 3 to +3, then the skewness of the dataset is within the range of normality (Onwuegbuzie&Daniel, 2002). If the resulting calculation is outside of this +/3 range, the dataset is not normally distributed.
 * Kurtosis [Note. Kurtosis also refers to the extent to which the data are normally distributed around the mean. This time, the data are piled up higher than normal around the mean or piled up higher than normal at the ends of the distribution.] Readers are referred to the following sources for a more detailed definition of kurtosis:
 To standardize the kurtosis value so that its value can be constant across datasets and across studies, the following calculation must be made: Take the kurtosis value from the SPSS output and divide it by the Std. error of kurtosis. If the resulting calculation is within 3 to +3, then the kurtosis of the dataset is within the range of normality (Onwuegbuzie&Daniel, 2002). If the resulting calculation is outside of this +/3 range, the dataset is not normally distributed.

(External Link)&term_id=326

(External Link)
 * Continue
 * OK
 √ Charts (these are calculated only if you wish to have visual depictions of skewness and of kurtosisthey are not required)
 * Histogram~ with normal curve (not required, optional)
 √ Continue
 √ OK

Note : Before you continue to another application you must complete the following:
 √ Data
 √ Split Files
 √ Analyze all cases, do not create groups
 √ OK
Step two:
Check for Skewness and Kurtosis values falling within/without the parameters of normality (3 to +3). Note that each variable has its own skewness value and its own kurtosis value. Thus, a total of three standardized skewness coefficients and three standardized kurtosis coefficients can be calculated from information in the table below.
Skewness and Kurtosis Coefficients


CH005TC09R 
CL005TC09R 
CW005TC09R 
N 

Valid 
3125 
1805 
1877 
Missing 
5197 
6517 
6445 
Skewness 
1.129 
.479 
2.197 
Std. Error of Skewness 
.044 
.058 
.056 
Kurtosis 
1.818 
.412 
6.991 
Std. Error of Kurtosis 
.088 
.115 
.113 
Questions & Answers
algebra 2 Inequalities:If equation 2 = 0 it is an open set?
or infinite solutions?
Kim
if A not equal to 0 and order of A is n prove that adj (adj A = A
rolling four fair dice and getting an even number an all four dice
Differences Between Laspeyres and Paasche Indices
No. 7x 4y is simplified from 4x + (3y + 3x) 7y
J, combine like terms 7x4y
im not good at math so would this help me
how did I we'll learn this
Need to simplify the expresin. 3/7 (x+y)1/7 (x1)=
. After 3 months on a diet, Lisa had lost 12% of her original weight. She lost 21 pounds. What was Lisa's original weight?
preparation of nanomaterial
Yes, Nanotechnology has a very fast field of applications and their is always something new to do with it...
can nanotechnology change the direction of the face of the world
At high concentrations (>0.01 M), the relation between absorptivity coefficient and absorbance is no longer linear. This is due to the electrostatic interactions between the quantum dots in close proximity. If the concentration of the solution is high, another effect that is seen is the scattering of light from the large number of quantum dots. This assumption only works at low concentrations of the analyte. Presence of stray light.
the Beer law works very well for dilute solutions but fails for very high concentrations. why?
how did you get the value of 2000N.What calculations are needed to arrive at it
Got questions? Join the online conversation and get instant answers!
Source:
OpenStax, Calculating basic statistical procedures in spss: a selfhelp and practical guide to preparing theses, dissertations, and manuscripts. OpenStax CNX. Apr 28, 2011 Download for free at http://cnx.org/content/col11292/1.6
Google Play and the Google Play logo are trademarks of Google Inc.