Chi+Square+with+Candy.pdf.Kami

pdf

School

UEI College, Gardena *

*We aren’t endorsed by this school

Course

MEDICAL BI

Subject

Statistics

Date

Apr 3, 2024

Type

pdf

Pages

Uploaded by ChefScienceWombat32

Name:___________________________________________ Date: ______ Chi Square (X 2 ) Modeling Using Candy The Chi Square test is often used in science to determine if data you observe from an experiment is close enough to the predicted data. In genetics, for instance, you might expect to get a 75% to 25% ratio if you crossed two heterozygous tall plants (Tt x Tt). Calculating the X 2 values help you determine whether the results follow the prediction and if the variations from the exact ratio are due to random chance. It's the question of "how close is close enough?" If the numbers differ greatly from your expected results, then it's possible that other factors may be influencing your results. The Chi-square test is intended to test how likely it is that an observed distribution is due to chance. It is also called a "goodness of fit" statistic, because it measures how well the observed distribution of data fits with the distribution that is expected if the variables are independent. Another way to describe the Chi-square test is that it tests the null hypothesis that the variables are independent, that there is no relationship between the two things being tested. Wherever the observed data doesn't fit the model, the likelihood that the variables are dependent becomes stronger, thus proving the null hypothesis incorrect! Question: Do Companies Selling Candy Equally Distribute Candy Colors in Bags? Null Hypothesis: Candy is evenly distributed, each bag contains the same number of colors. Alternate Hypothesis: One (or more) color is found in greater frequency. Materials: several bags of colored candy, such as M & M's, Skittles, Reese's Pieces, or Gummy Bears. You will need approximately 100-200 candies. Procedure: *Go to page 3 1) Look into the bag and determine how many colors are present and write them into Table 1 2) Without counting, estimate the number (percentage out of 100%) of each if they are all evenly sorted to packages. This is your “Percentage Estimate.” 3) Sort the candy and write down the number of each color into Table 1 under "Number Observed" 4) Complete the table by determining the total number of candies and "number expected" columns Color of Candy Percentage Estimate Number Observed Number Expected (total # of candy x percentage estimate) Total # of candies =

As you look at the data above, consider the two comparable numbers. The number you would expect to count if your percentage estimate was correct, and then the number you actually counted (number observed). For example, if you initially thought that you'd see 25% yellow candies, and you counted 200 pieces, you would then expect to see 50 yellow candies. You may have only counted 40 yellows. The Chi Square (X 2 ) Equation In order to complete the calculation, you sum each of the traits (colors) that you measured. To help you with this, we will break the process into steps Classes (colors) Expected (e) Observed (o) (o - e) 2 / e 1 2 3 4 5 6 Sum (add the values from row 1-5); this is your X 2 value Use the chi square chart below to determine if your X 2 supports or rejects your hypothesis. The degrees of freedom is determined by subtracting 1 from the number of colors you analyzed. (For example, if you had 4 colors to count, the degrees of freedom is 3) Summary and Analysis 1) What was your initial hypothesis? 2) How do you show that your hypothesis is correct (or incorrect)? 3) Explain what is meant by a "good fit"? 4) Propose a way that a chi square analysis could be used in other experiments, such as genetics or drug trials.

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

Related Documents

Problem Set 2 Answers.docx

Lab Assignment Template (2) (Repaired).docx

Lab Assignment 1.pdf

ICA6.docx

Exam 1 Stats Lab-2.docx

HK 368 Lab 6-Olivia Keesling.pdf

Recommended textbooks for you

Algebra & Trigonometry with Analytic Geometry

Algebra

ISBN:9781133382119

Author:Swokowski

Publisher:Cengage

College Algebra

Algebra

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:Cengage Learning

Algebra and Trigonometry (MindTap Course List)

Algebra

ISBN:9781305071742

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:Cengage Learning

SEE MORE TEXTBOOKS

Recommended textbooks for you

Algebra & Trigonometry with Analytic Geometry
Algebra
ISBN:9781133382119
Author:Swokowski
Publisher:Cengage
College Algebra
Algebra
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning
Algebra and Trigonometry (MindTap Course List)
Algebra
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:Cengage Learning