Statistics By Rajat: Statistics and Research to Help

                                                   FFrequency & Frequency Distribution It tells how often something happened.The frequency of an observation tells you the number of times observation occur in the data. For e.g, the frequency of number  5 is 4. ,5,2,5,6,5,2,4,5,8,5. Frequency Distribution: It is representation of data or you can say observation within the given interval. Example: Newspapers These are the numbers of newspapers sold at a local shop over the last 10 days: 22, 20, 18, 23, 20, 25, 22, 20, 18, 20 Let us count how many of each number there is: Papers Sold Frequency 18 2 19 0 20 4 21 0 22 2 23 1 24 0 25 1 Papers Sold Frequency 15-19 2 20-24 7 25-29 1 Grouped Frequency Data: When the data is sorted and classified into classes, then it is called as Grouped frequency data. For e.g. you can refer to this:   https://www.statisticshowto.com/grouped-data/ .

Range: It is the difference between the highest and the lowest value. for example, 1. Range(team 1): 17.5 - 10.5 = 7 2.  Range(team 2): 27.7 - 0 = 27.7 As ranges takes only the count of extreme values sometimes it may not give you a good impact on variability.  In this case, you can go for another measure of variability called interquartile range (IQR). Interquartile Range (IQR):  It is a better measure of dispersion than  range  because  it leaves out the extreme values . It equally divides the distribution into four equal parts called quartiles. First 25% is 1 st  quartile (Q1), last one is 3 rd  quartile (Q3) and middle one is 2 nd  quartile (Q2). 2 nd  quartile (Q2) divides the distribution into two equal parts of 50%. So, basically it is same as  Median. How to calculate IQR: Step 1: Order from low to high Step 2: Find the median or in other words Q2 Step 3: Then find Q1 by looking the median of the left side of Q2 Steps 4: Similarly find Q3 by looking the median of the right of Q

MMEAN,MEDIAN AND MODE In order to summarize your data, you can do this using two methods : Graphs. Central Tendency methods. 1 . Graphs: Using various graphs we can easily summarize our data and get into the result. 2. Central Tendency Method: It represents the center point or typical value of dataset. It represents the data to cluster to a middle value.   Measures of Central Tendency I t can be measured through three different: 1. Mean 2. Median 3. Mode 1. Mean: It is one of the common central tendency method used.It can used for discrete and continuous data.It is given by sum of all values of dataset divided by number of values in the dataset. So if we have n values in dataset and they have values like x1,x2,x3,x4 etc.                                               Mean Formula – Example #1 Let say you have a data set with 10 data points and we want to calculate mean for that.  Data set : {4,6,8,9,22,83,98,45,87,10} 2.  Median: The median is the middle score for a set of data that h

STATISTICS It is science of  data which is mainly concerned with collection,organizing,analysis and interpretation of data by providing suitable conclusion. For eg. data from healthcare, data of company sales. Some terminology of Statistics: 1. Data: It is collection of meaningful information presented in proper format.                                                                                           1.Primary Data: The data which is collected by  directly asking the questions related to research to people or respondent  and recording the responses. Some research do this by going on ground and asking to respondent and collecting data.For e.g. Take the election exit-pool where the company asks voters whom they voted,collect all data and prepare necessary conclusion,then they sell their conclusion to various news agency whom they  had tie-up. 2. Secondary  Data: T he data which can be collected through other sources, as the company collect it from research or data-collection wh