. Ans:Spearmans rank correlation coefficient formula is\({r_s} = 1 \frac{{6\sum\limits_{i = 1}^n {d_i^2} }}{{n\left( {{n^2} 1} \right)}}\)Here, number of paired observations, \(n=8\)\({r_{\rm{s}}} = 1 \frac{{6\sum {{\rm{d}}_{\rm{i}}^2} }}{{{\rm{n}}\left( {{{\rm{n}}^2} 1} \right)}}\)\( = 1 \frac{{6 \times 22}}{{8 \times 63}}\)\( = 1 \frac{{132}}{{504}}\)\( = \frac{{372}}{{504}}\)\(\therefore {r_s} = 0. in Statistics Mathematics. Step 4- Add up all your d square values, which is 12 (∑d square)Step 5- Insert these values in the formula =1-(6*12)/(9(81-1))=1-72/720=1-01=0. Spearman Rank Correlation Coefficient tries to assess the relationship between ranks without making any assumptions about the nature of their relationship.

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A zero correlation coefficient indicates no correlation between the two variables. The correlation coefficient is the number indicating the how the scores are relating. 5\) is taken. Usually judges award numerical scores for each contestant after his/her performance. Then find out the square of the difference in the ranks given to the two variables values for each item of the data.

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Here is how the calculations work: The scores of 9 students in History and Geography are mentioned in the table below. 714\)The value of \(r\)indicates a strong negative coefficient of correlation. The numerical value review the correlation coefficient, rs, ranges between -1 and +1. It is simple to understand and calculate.

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A Pearson correlation is a statistical measure of the strength of a linear relationship between paired data. . It is a rank correlation coefficient as it uses the rankings of data of each variable rather than the raw data. How do you do Spearman rank with tied ranks?Ans: When we have tied ranks or repeated ranks, wetake the mean or average of the same ranks. In such cases, rank correlation is used to determine the relationship between two characteristics. A product moment correlation coefficient of scores by the two judges hardly makes sense here as we are not interested in examining the existence or otherwise of a linear relationship between the scores.

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This could have two interpretations. 190. We will use spearmans rank correlation formula. The Spearman Rank Correlation Coefficient is its analogue when the data is in terms of ranks.

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It measures the monotonicity of a relationship between two variables, that is, how well a monotonic function can represent the relationship between two variables. com
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