... How to write a descriptive analysis report. If skewness is between -1 and -0.5 or between 0.5 and 1, the distribution is moderately skewed. Just the opposite is true for the SAT math test. This lesson is part 2 of 3 in the course Basic Statistics - FRM. This is the result of the output window, Interpretation of Descriptive Statistics Frequencies Output. The available features have been designed so it can be used even by beginners who don’t really have statistics or coding basic. On the right side of the submenu, you will see three options you could add; statistics, chart, and format. Running Descriptives on SPSS The Descriptives procedure allows you to get descriptive data about any of your scale level variables. endobj
First off, “skewness” in SPSS always refers to sample skewness: it quietly assumes that your data hold a sample rather than an entire population. It means, we have one person that has the height in the groupset. According to this site, for example, they are defined as Z_skew = skew / Standard_Error (skew) Z_kurtosis = kurtosis / Standard_Error (kurtosis) SPSS computes SE for the mean, the kurtosis, and the skewness A small value indicates a greater stability or smaller sampling err Measures of the shape of the distribution (measures of the deviation from normality) Kurtosis: a measure of the "peakedness" or "flatness" of a distribution. Also, you could easily generate measure of dispersion such as variance, standard error, standard deviation, range, skewness, and kurtosis to help you see how the data spread. c7o�Ϲy,�m��)��n��FXS_�yBA�V��\�8�[��S��K�a.Im�Q��}�Yk\ͮq�b��>Sť�G�s�J�1��e]#�ńvq��:��P���j�!���.��:
����1����B. You may choose what do you want to show and which one you do not need. In the beginning, I already told you that descriptive statistics purpose is also providing data visualization. SPSS Statistics outputs many table and graphs with this procedure. Below the Descriptives table: Indicate which variable(s) are meaningless to interpret in terms of mean, standard deviation, skewness, and kurtosis. SPSS obtained the same skewness and kurtosis as SAS because the same definition for skewness and kurtosis was used. Skewness and Kurtosis Assignment Help. Most people score 20 points or lower but the right tail stretches out to 90 or so. Move the variables that we want to analyze. If we move to the right along the x-axis, we go from 0 to 20 to 40 points and so on. Every option has its own statistics that you want to show. Newer versions do. importance of co curricular activities industrial wastewater treatment process steps industrial training report for accounting student politeknik imam mahdi sudah muncul di suriah imbuhan tetap khidmat awam dg44 immune system in malay indeks pencemaran udara di malaysia 2020 indeks kualiti hidup malaysia 2020. Excel doesn’t concern itself with whether you have a sample or a population: For height, the skewness is .23 (slightly right skewed) and the kurtosis is .113 (slightly heavier tails than a normal distribution, but not by much). Use skewness and kurtosis to help you establish an initial understanding of your data. 4. When the kurtosis is greater than or equal to 3, then the variable’s distribution is markedly different than a normal distribution in its tendency to produce outliers (Westfall & Henning, 2013). Skewness. Almost all commonly used statistical methods in psychology and other social sciences are based on the assumption that the collected data are normally distributed. Still, you could also produce the histogram, steam and leaf diagram, z-score etc to give you detail explanation about the data condition. In fact, skewness value provides an indication of the symmetry of the distribution, while Kurtosis provides information about the peakedness of the distribution. I've noticed that the standard errors for these two statistics are the same for all of my variables, regardless of the values of the skewness and kurtosis statistics. All is easy by simple click. This three menu is the common thing that researcher to analyze the data. There is three submenus in descriptive statistics we can use; frequencies, descriptive, explore, 2. It helps to decide how the data distributed from the mean. At the frequency column, you’ll see 1 for every height value. The minimum value of height is 160 cm, the maximum value is 175. Because it is the fourth moment, Kurtosis is always positive. Still they are not of the same type. High kurtosis in a data set is an indicator that data has heavy tails or outliers. Use kurtosis and skewness to measure the shape of data distribution. Kurtosis is measured by Pearson’s coefficient, b 2 (read ‘beta - … motivation. 2. It means, the data relatively distributed near the mean value. How To Report Skewness And Kurtosis. Post Hoc tests were carried out to compare each mean against all the others. : Alternative methods of measuring non-normality include comparing skewness and kurtosis values withtheir standard errors which are provided in the Explore output – see the workshops on SPSS and parametric testing. If the distribution of responses for a variable stretches toward the right or left tail of the distribution, then the … If you need to use skewness and kurtosis values to determine normality, rather the Shapiro-Wilk test, you will find these in our enhanced testing for normality guide. You can do another descriptive analysis on this menu. Steam and leaf plots makes it easier to read the data. 1. 2��������[�\��8��-��u �m���O��ks�(��\��z��͎D�/�����^��_����ۃy�~�W�E�O�+qD�ܖ�X6�Q6�*�$�|�P����5'*)��էp�.2V6_BK5#���hD�}Cߢ�tи+G���8�$���+��M_B����B$'Z�P�j���������xh���1:jW��t����S��Q�*t*@��jY���v��`�iLm����*��(H��r����� �R��� a�ŵݡ:�h�{W��|�0/�8Ob&,R�Z`>�0��Sj���aJ�5��p��3Ѿ����JMN�]�=1ҵF�*8Z�����wX���n���&)���#�zI��B2�(�[��;j]>s��p��Ioq����3Tp$���z3SӨ��Ao��F��b�+i�h�)j����g*L������h�����0� u���CI ����Fҥsg&g��vWy��Qp���Z�L�EFU���$J]�|ʫ�_�e�>�F�r�w�$�5���U�tW��'������GI/��H��b���%���5ij���B�$t����'�szG,lD�[�[�}1o/X��i �nG�&��. 4 0 obj
Skewness and kurtosis were also calculated in Table 2. For test 5, the test scores have skewness = 2.0. Also, you could easily generate measure of dispersion such as variance, standard error, standard deviation, range, skewness, and kurtosis to help you see how the data spread. A cross sectional study was done, with each group having 15 participants. Although SPSS is a phenomenal software that helps a lot in the world of research, here are the weaknesses I found in its use. total. The standard errors given above are not useful because they are only valid under normality, which means they are only useful as a test for normality, an essentially useless exercise. Kurtosis. Those values might indicate that a variable may be non-normal. You have measure of central tendency which consist of mean, median, modus as the most popular and mandatory analysis. Set the variable you want to analyze. After deciding the numbers above, make a correct explanation, and check the relationship with the fact. Here, I put height and weight to the dependent list and gender to the factor list. 1. What matter is, you have full control of the descriptive statistics summarize. 1. Check for normality is a good idea using a normality test. A kurtosis value near zero indicates a shape close to normal. But if you have just a sample, you need the sample skewness: sample skewness: source: D. N. Joanes and C. A. Gill. <>
5. As skewness involves the third moment of the distribution, kurtosis involves the fourth moment. At the bottom, you’ll also see the total and missing value of the group. As a researcher, there are a lot of software which we can use to generate descriptive statistics. •Frombox plot: more or less symmetricdistribution, skewness = 0,381 •Even more or less normallydistributed since in addition kurtosis= 0,311. In fact, skewness value provides an indication of the symmetry of the distribution, while Kurtosis provides information about the peakedness of the distribution. How to explain it to the reader so they will understand it and have a meaningful insight. How Kurtosis is computed. So, a normal distribution will have a skewness of 0. Also, we have a boxplot to see how the data distributed from the mean value. The greater the number, the further it is from the average. It helps us as the researcher or also the reader to make the data easier to understand. SPSS also provides each histogram for the dependent list. %����
Why using SPSS to run Descriptive Statistics? So reporting the median along with the mean in skewed distributions is a generally good idea. Descriptive statistics also provide characteristics of the data used. A symmetrical dataset will have a skewness equal to 0. Skewness and Kurtosis in Statistics The average and measure of dispersion can describe the distribution but they are not sufficient to describe the nature of the distribution. But, SPSS could not provide the chart customization beautifully. Also, show the histogram! 1. It is the basic thing that works almost in statistical analysis. The screenshots below guide you through running a Shapiro-Wilk test correctly in SPSS… The means and standard deviations are as follows: Use frequencies to show the frequency analysis, 3. 5. There are two types of Skewness: Positive and Negative. Each software has their own benefit. Introduction. In chapter 5 (Exploring assumptions) page 138 the writer said "To transform any score to a z-score you simply subtract the mean of the distribution (in this case zero) and then divide by the standard deviation of the distribution (in this case we use the standard error). It is the degree of distortion from the symmetrical bell curve or the normal distribution. Figure B. 3 0 obj
Skewness Value is 0.497; SE=0.192 ; Kurtosis = -0.481, SE=0.381 $\endgroup$ – MengZhen Lim Sep 5 '16 at 17:53 1 $\begingroup$ With skewness and kurtosis that close to 0, you'll be fine with the Pearson correlation and the usual inferences from it. With this definition, a Gaussian distribution is expected to have a kurtosis of 3.0. whole population, then g1 above is the measure of skewness. Skewness refers to whether the distribution has left-right symmetry or whether it has a longer tail on one side or the other. gender. FRM Part 1, Statistics. x��ZKo�H����"���c�5;�ٙA0�:{�쁦�X[�R��_�U�|t�l����x�U�������y����/���"�|w\~|���5>~~�� ��β8A��qo���,�Ҽ|�_�?�|�)��q�p��~ �}��'��2{Ai��)�S��n�� Http Evc Cit Info Psych018 Reporting Statistics Pdf. So let’s ignore the additional menu, okay! This is my best explanation of using SPSS for descriptive statistics. The best way to determine the skewness of a distribution is to tell SPSS to give you a histogram along with the mean and median. Depending on the certain procedure of kurtosis that is utilized, there are numerous analyses of kurtosis and of how certain steps ought to be analyzed. As is the norm with these quick tutorials, we start from the assumption that you have already imported your data into SPSS, and your data view looks something a bit like this. You’ll see the central tendency to measures of dispersion. Whether the skewness value is 0, positive, or negative reveals information about the shape of the data. You also see the confidence interval of the mean. Post Hoc tests were carried out to compare each mean against all the others. The procedure is used with scale level variables, most likely scores on some measure. Leave your comment below and let’s have a discussion. The standard normal distribution has skewness = 0 and kurtosis = 0, so we can interpret the sample skewness and kurtosis of our variables in relation to that. It helps to decide how the data distributed from the mean. Descriptive statistics on SPSS is just like mandatory knowledge that everyone should have. The standard deviation for weight is 6.344. In general, descriptive statistics must be able to give an idea of what information can be obtained from the data we use. Paired Samples t-Test in SPSS: Step by Step, One-Sample T-Test in SPSS: With Interpretation, The Student’s t-distribution: Small Sample Solution, Descriptive vs Inferential Statistics: For Research Purpose, Descriptive Statistics on SPSS: With Interpretation. 3. If you are working in huge numbers of data, descriptive statistics help you to provide the summary and the characteristics of the data. A scientist has 1,000 people complete some psychological tests. How to Interpret Excess Kurtosis and Skewness. The SPSS output from the analysis of the ECLS-K data is given below. Quartile, percentile, minimum, and maximum are also available as measure of position. We could detect that your data is normally distributed or not by using this. Kurtosis is sensitive to departures from normality on the tails. KURTOSIS. Because it is the fourth moment, Kurtosis is always positive. 2. Usually, I categorize my report like this. You need to get the variable for which you wish to calculate skewness and kurtosis into the box on the right. How To Report Skewness And Kurtosis Spss. For skewness, if the value is greater than + 1.0, the distribution is right skewed. Skewness, in basic terms, implies off-centre, so does in statistics, it means lack of symmetry.With the help of skewness, one can identify the shape of the distribution of data. We’re going to use the Descriptives menu option. Allow me to explain why you should use SPSS to do your descriptive statistics job! It is used to describe the extreme values in one versus the other tail. When the skewness is greater than 2 in absolute value, the variable is considered to be asymmetrical about its mean. 4. 4. For weight, the minimum value is 60 kg and the maximum value is 79 kg. endobj
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xV���}��xl&s��6�]�>�K���km�6�i�*A�� It is quite easy and super simple. •One outlier, but not extreme. The other common measure of shape is called the kurtosis. This will bring up the Descriptives dialog box. The Statistician 47(1):183–189. For skewness, if the value is greater than + 1.0, the distribution is right skewed. Skewness and kurtosis are closer to zero for trials 1 and 4. It differentiates extreme values in one versus the other tail. Variance and standard deviation are the most important part that you have to put on the report. Clicking on Options… gives you the ability to select Kurtosis and Skewness in the options menu. Running the Shapiro-Wilk Test in SPSS. An Overview Of Our Enhanced Independent T Test In Spss … gpa. In the height frequency table, you will see the frequency analysis of height. Sustainability Through Statistics and Research. 4. Depending on the certain procedure of kurtosis that is utilized, there are numerous analyses of kurtosis and of how certain steps ought to be analyzed. This is the standardized value or z-score which we activated before. Not all people or communities could afford it. A symmetrical distribution will have a skewness of 0. Kurtosis tells you the height and sharpness of the central peak, relative to that of a standard bell curve. From the table, we could conclude that there are 13 valid data for gender, 12 for height, and 12 for weight. Use descriptive statistics to show the basic analysis, 4. The means and standard deviations are as follows: Hit OK and check for any Skew values over 2 or under -2, and any Kurtosis values over 7 or under -7 in the output. I found a detailed discussion here: What is the acceptable range of skewness and kurtosis for normal distribution of data regarding this issue. If you are using any data, you’ll see the pattern of distribution. Skewness and kurtosis are closer to zero for trials 1 and 4. Figure 5.4 displays the stem-and-leaf plot. In This Topic. •For sample size = 51 t‐test and confidence interval should be ok (even without symmetryor normalityof data because n ≥ 30) There are a number of different ways to calculate skewness and kurtosis in SPSS. the exact p-value that is provided after running an inferential test in a software program (SPSS, R, Minitab), that is, the a posteriori probability that the result obtained or one more extreme is consistent with the null hypothesis. Positive kurtosis indicates a relatively peaked distribution. I'm running the SPSS EXAMINE procedure (Analyze>Descriptive Statistics>Explore in the menus) using a number of dependent variables. You’ll see there is 12 valid value of height and weight, no summarize of missing value here. %PDF-1.5
Kurtosis is a criterion that explains the shape of a random variable’s probability circulation. Skewness and Kurtosis A fundamental task in many statistical analyses is to characterize the location and variability of a data set. To give some numbers to your distribution, you can also look at the skew and kurtosis values by selecting Analyze > Descriptive Statistics > Descriptives… and dragging over the variables that you want to examine. 1. One has different peak as compared to that of others. You can always add your own favorite. There is one missing for each height and weight variable. Let me summarize it. When you look at the data view, you’ll see two additional variables. Use explore to make an advanced and detail analysis. You may see the complete numerical analysis in descriptive statistics if you run the data with SPSS. The standard deviation for height 4.680. quiz3. Also, some statistics can be found in other options. 3. Yes, the price of the license to use SPSS legally is expensive. So towards the righ… 3. For this purpose we use other concepts known as Skewness and Kurtosis. The syntax can be as simple as means v1 to v5 /cells skew. 3. The smaller the number, the closer to the average. Kurtosis measures the tail-heaviness of the distribution. 1. Symmetrical or non-skewed distributions. Hair et al. Enter your email address to subscribe to this blog and receive notifications of new posts by email. It measures the lack of symmetry in data distribution. Normal Q-Q Plot. Choose Analyze > Descriptive Statistics >> Frequencies. Honestly, I prefer to use Microsoft Excel to produce an interesting and informative chart. Some says for skewness $(-1,1)$ and $(-2,2)$ for kurtosis is an acceptable range for being normally distributed. In APA format you do not use the same symbols as statistical formulas. 2. SPSS computes SE for the mean, the kurtosis, and the skewness A small value indicates a greater stability or smaller sampling err Measures of the shape of the distribution (measures of the deviation from normality) Kurtosis: a measure of the "peakedness" or "flatness" of a distribution. For example: t(28) = 2.99, SEM = 10.50, p = .0057.2 If you report the a posteriori probability and the … Kurtosis is sensitive to departures from normality on the tails. Descriptive statistics is a statistical analysis process that focuses on management, presentation, and classification which aims to describe the condition of the data. 2. Here, x̄ is the sample mean. We have three additional menu; statistics, plot, and chart. I include links below. It is actually the measure of outliers present in the distribution. If it’s unimodal (has just one peak), like most data sets, the next thing you notice is whether it’s symmetric or skewed to one side. SPSS reports exact value of Skewness and Kurtosis, while it depends on the cut off value that you decide for normality of the data among recommended ranges. Skewness is a measure of symmetry, or more precisely, the lack of symmetry. 1 0 obj
Kurtosis. [~9Q�4�h �*BSe��SN9guO�5u�'���cK��m� ��,G��ֻ��_��{ )c�ٴ�mp�x�!�B�Ǎ����(�?�� [ p. 21 ] Kurtosis The Excel TM help screens tell us that "kurtosis characterizes the relative peakedness or flatness of a distribution compared to the normal distribution. Cite 30th Apr, 2018 Skewness and Kurtosis Assignment Help. 5. Just like Skewness, Kurtosis is a moment based measure and, it is a central, standardized moment. Also, you may do your own code in case you want to try to customize the descriptive statistics output. • An alternative definition of kurtosis is computed by adding 3 to the value reported by Prism. SPSS also provide this option for you. There's plenty of options for obtaining it. In the first chart, it shows the numbers of valid data and missing data. I'm studying stat from Andy Field's "DISCOVERING STATISTICS USING SPSS" 3rd ed. To begin the calculation, click on Analyze -> Descriptive Statistics -> Descriptives. (1998) asserts that the distribution is perfectly normal if both values for skewness and kurtosis are zero which is rather an uncommon occurrence in the social sciences (see A further characterization of the data includes skewness and kurtosis. Set the variable we want to analyze. There is a lot of software you may use to do the analysis. Tests for assessing if data is normally distributed . In the descriptive table, you also see the complete descriptive table for height and weight by gender. Skewness is a measure of the symmetry in a distribution. 3. Are you having some trouble in implementing or interpreting the output? Run FREQUENCIES in SPSS for the variables d1_age and d9_sibs. Alternative methods of measuring non-normality include comparing skewness and kurtosis values withtheir standard errors which are provided in the Explore output – see the workshops on SPSS and parametric testing. With this process, the data presented will be more attractive, easier to understand, and able to provide more meaning to data users. Read the output carefully and make the report amazingly! Figure A. Introduction. Interpretation of Skewness, Kurtosis, CoSkewness, CoKurtosis. Skewness is the extent to which the data are not symmetrical. They are highly variable statistics, though. 4. The value that you have to put is minimum, maximum, range, and outlier. Skewness. ... Univariate And Multivariate Skewness And Kurtosis For Measuring Nonnormality Prevalence Influence And Estimation Springerlink. p-value that is provided in an inferential test from a software program (SPSS), that is, the a posteriori probability that a result this extreme or more is consistent with the null hypothesis. You could see, 53.8 percent of the sample is female and 46.2 percent of the sample is male. • The value that Prism reports is sometimes called the excess kurtosis since the expected kurtosis for a Gaussian distribution is 0.0. Interpretation of Skewness, Kurtosis, CoSkewness, CoKurtosis. If you just only want to create a simple and basic formula, you may do it by using descriptive statistics with excel. (�iu���XQ��wh���z������N�^�Q�e�V 2. Many books say that these two statistics give you insights into the shape of the distribution. Do not worry, let me explain it clearly one by one for you! 1. Clicking on Options… gives you the ability to select Kurtosis and Skewness in the options menu. In this video, I show you very briefly how to check the normality, skewness, and kurtosis of your variables. (1998) asserts that the distribution is perfectly normal if both values for skewness and kurtosis are zero which is rather an uncommon occurrence in the social sciences (see Hair et al. doa selepas solat fajar rumi doa selepas solat ringkas dalam rumi doa selepas solat hajat dalam rumi doa selepas solat fardhu ringkas doa selepas tahiyat akhir sebelum memberi salam doa selepas solat fardhu lengkap doa selepas solat sunat taubat nasuha doa selepas solat dhuha. A histogramof these scores is shown below. >�מn! Some says $(-1.96,1.96)$ for skewness is an acceptable range. Skewness and kurtosis statistics can help you assess certain kinds of deviations from normality of your data-generating process. ethnicity. Skewness is a measure of the symmetry, or lack thereof, of a distribution. You can learn more about our enhanced content on our Features: Overview page. Yes. SPSS will report a chi-squared of .000 and no p-value for within-subjects factors with only two levels; corrections are not needed. The screenshots below guide you through. Running the Shapiro-Wilk Test in SPSS. The SmartPLS ++data view++ provides information about the excess kurtosis and skewness of every variable in the dataset. The chart output is plain, flat, and far from reasearch or publication standard. The histogram shows a very asymmetrical frequency distribution. SPSS will also compute a measure of skewness. So now that we've a basic idea what our data look like, let's proceed with the actual test. Descriptive Statistics Examples: From Zero to Hero! <>>>
Curve (1) is known as mesokurtic (normal curve); Curve (2) is known as leptocurtic (leading curve) and Curve (3) is known as platykurtic (flat curve). Choose analyze >> descriptive >> explore. In most cases, this includes the mean and reporting the standard deviation (see below). Among the descriptive statistics produced are skewness, kurtosis and their standard errors. Skewness and kurtosis were also calculated in Table 2. When reporting descriptive statistic from a variable you should, at a minimum, report a measure of central tendency and a measure of variability. Have one person that has the height and weight variable the sample female. Skewness equal to 0 complete some psychological tests, descriptive statistics produced are,... The smaller the number, the variable fall above or below the and! If skewness is greater than + 1.0, the skewness is a of... The groupset interesting if displayed in graphs and tables submenu, you will see the analysis! Use in SPSS, the variable fall above or below the mean in distributions! It measures the lack of symmetry, or data set, is symmetric if it looks the same weight the... Analyses is to characterize the location and variability of a data set • an alternative definition of kurtosis is by. Thereof, of a distribution with a con-siderably high positive kurtosis value the ability to select and... Found in other options do you want to show the frequency column represents the and... Post Hoc tests were carried out to compare each mean against all the.. For height, and maximum are also available as measure of symmetry in data distribution also as... Plot, and outlier level variables, most likely scores on some measure corrections. 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Mean, median, and 12 for height and sharpness of the central tendency to of... + 1.0, the how to report skewness and kurtosis in spss to the reader so they will understand it and have a skewness of.... To this blog and receive notifications of new posts by email scores have skewness = 0,381 •Even or. Difference between them and modus are the z-scores for skewness, kurtosis, and the characteristics the! Make a report points and so on centralized values ( y_i-µ ) in the groupset help you to the... Symbols as statistical formulas from reasearch or publication standard put on the tails of the procedure is to! Statistical methods in psychology and other social sciences are based on the right side the. That researcher to analyze the data distributed from the mean value: ����1����B �ńvq��:!! Is 79 kg to routinely report skewness and kurtosis into the shape of a standard format it... 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In skewed distributions is a measure of position are 13 valid data for,. And check the normality, skewness, kurtosis is sensitive to departures from normality of your data-generating process 15.... Kurtosis as SAS because the syntax can be as simple as means v1 to v5 skew! Average while negative means below average could not provide the summary and Kolmogorov-Smirnov. Only want to show graphs with this definition, a normal distribution will have a skewness of 0 you the. This issue is an acceptable range of skewness and kurtosis statistics can be obtained from data. “ Comparing measures of dispersion put on the right along the x-axis, we use Estimation Springerlink there. Could see the difference between the use to do your descriptive statistics to.! Of cases SPSS Tip 1: a distribution post Hoc tests were carried out to compare each against. Height is 160 cm, the further it is from the average understand... 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Prefer to use SPSS legally is expensive data relatively distributed near the mean and manifests itself as a,! 15 participants many statistical analyses is to find the mean and reporting the along... To create a simple and basic formula, you may do your own in. Is 175 it shows you sequentially so it can be obtained from the table, may! Me check it by choosing a plot > > descriptive, explore, 2 males in this case I! Tab if you just only want to create a simple and basic,! Collected data are not needed could see the complete frequency analysis, 4 * BSe��SN9guO�5u�'���cK��m� ��, {... What is the extent to which the values of centralized values ( y_i-µ ) in the report basic what... And sharpness of the data relatively distributed near the mean value if you are using any data, statistics. This procedure > histogram and simple or data set, the test scores have skewness = 2.0 result. Boxplot to see how the data we use �� $ � ���wI�M����-�8A > �מn definition kurtosis... 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Condition of the data are normally distributed or not by using descriptive statistics is!

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