Compute the expected counts for each color. A manufacturer of colored candies states that 13% of the candies in a bag should be brown, 14% yellow, 13% red, 24% blue, 20% orange, and 16% green. A student randomlyselected a bag of colored candies. He counted the number of candies of each color and obtained the results shown in the table. Test whether the bag of colored candies follows thedistribution stated above at a = 0.05 level of significance. Using the level of significance a = 0.05, test whether the color distribution is the same.Click here to view the table. Click here to view the table of critical values of the chi-square distribution.The incivis is its un an stated by the manufacturiOC. Ho: The distribution of colors is at most as uniform as stated by the manufacturer.H,: The distribution of colors is more uniform than stated by the manufacturer.D. Ho: The distribution of colors is the same as stated by the manufacturer.H₁: The distribution of colors is not the same as stated by the manufacturer.Compute the expected counts for each color.ColorBrownYellowRedBlueOrangeGreenFrequency596557599964Expected Count(Round to two decimal places as needed.) Observed Distribution of ColorsColorFrequencyClaimed ProportionColored Candies in a bagBrown Yellow Red Blue596557590.130.14 0.130.24PrintDoneOrange Green99640.200.16I

From given data we have : Expected fraction (p) Observed (O) 0.13 59 0.14 65 0.13 57 0.24…

A manufacturer of colored candies states that 13% of the candies in a bag should be brown, 14% yellow, 13% red, 24% blue, 20% orange, and 16% green. A student randomly selected a bag of colored candies. He counted the number of candies of each color and obtained the results shown in the table. Test whether the bag of colored candies follows the distribution stated above at a = 0.05 level of significance. Using the level of significance a = 0.05, test whether the color distribution is the same. Click here to view the table. Click here to view the table of critical values of the chi-square distribution.