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 ?What is the concept of statistics/ statistical analysis 

Statistics is the science of the process of collect, organize, interpret and analyze data. The science of statistics is a very important science in many fields of our live. Statistics is powerful in the fields of forecasting, genetics, medical and many others. The statistical analysis is a science that use statistics to perform patterns and trends. 

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 Characteristics of statistics/ statistical analysis 

Here are a very important characteristics of using statistics and statistical analysis which are:

• First, statistics/ statistical analysis sciences are a assemble of facts
• Second, statistics/ statistical analysis expressed by numerical values
• Third, statistics/ statistical analysis sciences are not collected with no reasons. But statistics/ statistical analysis collected with a predetermined reasons and goals.
• Fourth, statistics/ statistical analysis able to comparable to each other.
• Fifth, statistics/ statistical analysis using reasonable standard of accuracy to enumerate or estimate it.
• Sixth, statistics/ statistical analysis must be collected in a systematic technique.

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 How important the statistics/ statistical analysis? 

The science of statistics/ statistical analysis has many benefits in many fields in our live and generally the importance of statistics/ statistical analysis can be shows as follow:

• First, statistics/ statistical analysis helps to understand the meaning of raw data collected and its phenomena.
• Second, statistics/ statistical analysis helping to present complex data in a suitable form to understand what data/ data set means.
• Third, statistics/ statistical analysis provides you an understanding what does the data/ data set pattern means.
• Fourth, statistics/ statistical analysis helping in efficient planning of the statistical inquiry in your field of study.  

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 Basic statistics/ statistical analysis methods 

In this paragraph, you will deal with the basic statistics/ statistical analysis methods which you may use it in many fields of your study or in your life which are:

• First statistics/ statistical analysis method: Mean statistical analysis method
• Second statistics/ statistical analysis method: Standard deviation statistical analysis method
• Third statistics/ statistical analysis method: Regression statistical analysis method
• Fourth statistics/ statistical analysis method: Hypothesis testing statistical analysis method
• Fifth statistics/ statistical analysis method: Sample size determination statistical analysis method
• Sixth statistics/ statistical analysis method: Mode statistical analysis method
• Seventh statistics/ statistical analysis method: Median statistical analysis method

First statistics/ statistical analysis method: Mean

Mean method is the first and most popular used method in statistics/ statistical analysis. The Mean method is also referred as the average value of a given data/ data set.

Mean method can be evaluated for a data set (a group of numerical values). Thus, by summing up all the values and then divided the sum by the number of numerical values of the given data/ data set. For example, if you have a data set like this {5, 3,7,8 ,9,4}, then the Mean value equals (5+3+7+8+9+4)/6= 36/6 = 6 (the Mean equals 6 for the given data set).

The method of Mean is useful to determine the overall trends of a given data/ data set. Also, Mean method is a very easy and simple way to make statistical analysis so you can get a fast view of the given data set.

Disadvantage point in the Mean statistical method when you have outliers’ values or inaccurate distribution, then the result will be inaccurate.

Second statistics/ statistical analysis method: Standard deviation method

 Standard deviation method is the second statistical method which measures how data spreading around the mean value. The Standard deviation values can be evaluated by this role:

Role variable explanation:

SD: standard deviation variable                      X̄: the mean of the set

X: each value in a given data set                    N: number of values in the given data set

For example, the data set used above {5, 3,7,8 ,9,4} you can calculate the standard deviation as follow:

1. The mean value equals 6
2. To compute (X- X̄) the distance between each data set value from the mean value then square all each result:

Distance          squared distance

5 – 6 = -1         -1 * -1 = 1

3 – 6 = -3          -3 * -3 = 9

7 – 6 = 1            1 * 1 = 1

8 – 6 = 2            2 * 2 = 4

9 – 6 = 3            3 * 3 = 9

4 – 6 = -2        -2 * -2 = 4

• Summing up all the squared distances:

               Sum = 1+9+1+4+9+4= 28

• To calculate the variance value, you need to divide the above sum result by the number of data set values minus 1

              Variance = 28/ (6-1) = 28/5= 5.6

• Finally, calculate the standard deviation value by get the square root of the variance value

               SD =  = 2.36

The disadvantage point for standard deviation method when you use standard deviation only. With the existence of outliers values the method may provide inaccurate results

Third statistics/ statistical analysis method: Regression statistical method

The third statistical method is the regression method. Regression referred as a relationship between two variables (an independent variable and the other one is dependent variable). In the other word, regression means that how the changes on one variable can affected to make changes on the other variable. Regression cab be calculated as follow:

Y= a + b(x)

Y: this is the independent variable

A: is the y axis intercept when x=0

B: the slope

X: this is the dependent variable

Fourth statistics/ statistical analysis method: Hypothesis testing statistical method

Hypothesis testing is the fourth statistical analysis method. The Hypothesis testing method help to compare the given data/ data set against many assumptions and hypothesis. Its means that the hypothesis testing determine with of the tested arguments is true for a given data set.

Fifth statistics/ statistical analysis method: Sample size determination statistical method

Sample size determination is the fifth statistical method. This method is the best to use when you have a large amount of data or you have a big data set. But be careful here you need to use an appropriate size of data/ data set sample to get an accurate result from given data/ data set.

Sixth statistics/ statistical analysis method: Mode statistical method

Mode statistical method is the sixth method in statistical analysis. Mode value is the most value that appear mostly in a given data set. For example, if you a data set like this {5,4,8,2,1,4,5,4,1,5,4,8,4,7}

In the example above the mode equals 4 which is the most repeated value in a given data set.

Seventh statistics/ statistical analysis method: Median statistical method

Median statistical method is the seventh method in statistical analysis. Median is the value which placed in the middle/ center of a given data set. If you have a data set like this {2,4,5,7,8,9,4,3,6} this data set have an odd number of values. Which the number of values is 9 so the median value is the value that placed in the center of the data set (which here is 8). But if you have a data set with an even number of values, then the median is the average of two middle values. A data set like {4,7,8,7,3,4,5,4} here you have 8 values in the data set so the median equals (7+3)/2= 10/2 = 5 so the median equals 5.

Conclusion

1. The science of statistics/ statistical analysis conveys many important fields of our life.
2. There are many basic methods in statistical analysis to convert a raw data to a meaningful data.
3. Each of statistical method has own rule and purpose to use
4. The using of any statistical methods depends on the data/ data set itself.  

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 Video: Statistics made easy ! ! ! Learn about the t-test, the chi square test, the p value and more

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