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Paragraph 1 - The chi-squared test is commonly used in biological sciences. It enables us to assess the significance of differences between expected and observed data. The chi-squared value is a measure of the degree of deviation between expected and observed results on the basis of the null hypothesis; the larger the chi-squared value the larger the deviation between the expected and observed results.
For this reason, before calculating the chi-squared value, I prepared a null hypothesis, which states chance alone produces, any deviation between the observed and expected results. So my null hypothesis was that the rate of healing for the new drug X is equivalent to the rate of healing for the existing drug Y.
Paragraph 2 - The chi-squared test is commonly used in biological sciences. It is used to test data that cascades into distinct categories, in the form of discrete random variables. It is a measure of how closely the observed results correspond with the expected ones on the basis of the null hypothesis; the larger the chi-squared value the larger the deviation between the expected and observed results.
For this reason, before calculating the chi-squared value, I prepared a null hypothesis, which states chance alone produces, any deviation between the observed and expected results. So my null hypothesis was that the rate of healing for the new drug X is equivalent to the rate of healing for the existing drug Y.
For this reason, before calculating the chi-squared value, I prepared a null hypothesis, which states chance alone produces, any deviation between the observed and expected results. So my null hypothesis was that the rate of healing for the new drug X is equivalent to the rate of healing for the existing drug Y.
Paragraph 2 - The chi-squared test is commonly used in biological sciences. It is used to test data that cascades into distinct categories, in the form of discrete random variables. It is a measure of how closely the observed results correspond with the expected ones on the basis of the null hypothesis; the larger the chi-squared value the larger the deviation between the expected and observed results.
For this reason, before calculating the chi-squared value, I prepared a null hypothesis, which states chance alone produces, any deviation between the observed and expected results. So my null hypothesis was that the rate of healing for the new drug X is equivalent to the rate of healing for the existing drug Y.