BIO361H5 Lecture 5: Lec 5 - Sept 20

Introduction: A Chi-square test is used to compare observed data with expected data according to a hypothesis. For instance, if you were crossbreeding 2 heterozygous pea plants, you would expect to see a 3:1 phenotypic ratio in the offspring. In this case, if you were to breed 400 pea plants, you would expect to see 300 plants showing the dominant trait and 100 showing the recessive trait. But what happens if you observe only 260 plants with the dominant trait and 140 plants with the recessive trait? Does this mean something is wrong with Mendelian genetics or is this difference in expected results just due to chance (random sampling error)? These are the questions that can be answered using Chi-square statistics. The results of this statistical test is used to either reject or accept (fail to reject) the null hypothesis. The null hypothesis states there is no significant difference between the observed results and the expected results. This means that if the null hypothesis is accepted, the difference in observed and expected results was just a matter of chance and so the observed results basically "fit" with what was expected. Degrees of freedom (df) = number of independent outcomes (Y) being compared less 1 df = Y-1 At the 95% confidence interval we are 95% confident that there is a significant difference between the observed and expected results, therefore rejecting the null hypothesis. Probability Value - Is the decimal value determined from the X2 table and is the probability of accepting the null hypothesis. A 0.05 probability value equates to a 95% confidence interval.

The Chi-squared test formula is: Example: If we cross two pea plants that are heterozygous yellow pods, we would expect a 3:1 phenotypic ratio. So let's say we actually did the cross and got 280 plants with green pods and 120 plants with yellow pods. Question: Is this a 3:1 phenotypic ratio? This is the value of Chi-squared Test. We have a total of 400 plants and we expect a 300 green:100 yellow phenotypic ratio If the calculated Chi-squared value is less than the critical value listed in the Chi-squared table, then we accept the null hypothesis. This means that there is no significant difference between the observed and the expected values. Our degrees of freedom (df) = 2 outcomes - 1, or df = 1. Now we go the X2 table below and using the df = 1 and probability value of 0.05, our critical value is 3.84. Since our calculated X2 value is 5.33, and is larger than the critical value, we reject the null hypothesis and can say (at 95% confidence) that there is a significant difference between our observed and expected values.

The parent generation is yellowed podded and green podded pea plants. You cross a yellow podded pea plant with a green podded pea plant and you get 100% yellow podded plants in the F1 Generation (Phenotypic ratio 4 : 0, yellow to green). What will be the expected phenotypic ratio when you allow the F1 generation to reproduce?

Fill out the Punnett square.

If we actually did the cross and got 1150 yellow and 350 green. Would this be a consistent with what was expected?

Learning Outcomes Questions

1. Why would you run a Chi-squared test?

2. Determine the degrees of Freedom of the phenotypic ratio for this genetic cross.

a. 1

b. 2

c. 3

d. 4

e. 5

3. Using the data given, what is the result of your Chi-squared analysis? x2= ___.

4. Using the results of your Chi-squared analysis, do we fail to reject or reject the null hypothesis?

can anyone help with this really super basic lab? Feel free tomake up data, highschool level information please!

You are NOT limited to the suggested projects listed below.Think up your own unique research project!!

Projects should involve observation/measurement of livingorganisms-plants, animals, fungi, humans. They should be designedto answer a question or to test a hypothesis. Examples ofhypotheses would be; "Plants will grow more if there is morerainfall" Or "Students will get higher grades if they study more."Sample size is important when possible; make multiple measurementsof several individuals. Your project must be something thatproduces DATA that can eventually be graphed. There should be adependent variable and an independent variable. For example,"amount of rainfall" would be an independent variable and "how fastplants grow" the dependent variable.

Projects should take approximately three hours, total, tocomplete, not counting the write up, which will be a separate lab.Detailed instructions on writing your report are attached. Keepyour project simple and manageable. Submit your first project bythe due date for Project 12 (July 7th)**Please make sure that yourassignment gets to me by the due date. You will still be able toupload your assignment after the due date, but it will be marked aslate, and you will lose some points for being late.

A few examples of projects:

Is there a correlation between the size of a dog, and how longit lives? For this you will need about ten dead dogs! Ask aroundamong friends, classmates, family, about dogs that died a naturaldeath. Find out each dog's age at death, and approximate weight. Alarger sample size here would be even better. Can you explain thecorrelation?

Do humans have a physiological response (difference in pulse,blood pressure, etc.) to music? Choose three different categoriesof music, such as classical, folk, rock, or none (silence). Have atleast five people in your study, and measure their pulse (or bloodpressure) both before and after they have listened to the music for5-10 minutes. Graph the increase (or decrease) in their pulse forthe different types of music. GRAPH THE AVERAGE values for yoursubjects, not value for each individual.

Is there a correlation between a person's usual amount of sleep,and how well they perform on memory tasks? Devise a SIMPLE memorytest-it could be just to study a list of twenty random words, andthen to recall as many as possible. Give this test to at least fourpeople who usually get (a) less than 6 hours sleep, (b) 6-7 hourssleep and (c) 8 or more hours. Or, choose your own categories.Amount of sleep is your independent variable (X axis) and AVERAGEscores on the test, the dependent variable. (Y axis). GRAPH THEAVERAGE!

Include ALL relevant observations and information in precisedetail. If possible, include illustrations of your experiment, yoursubjects, your work in progress, etc.

Format for writing your Research Report:
1. Introduction

Lab Topic 1: The Process of Science

Introduction

1. Which of the following questions would you consider appropriate scientific questions that can be tested using the scientific method? For the statements that can be tested using the scientific method, explain how your experiment would be set up. Explain the different steps in the scientific method as they relate to this statement.

a. Does the pH of the soil affect the color of hydrangea flowers?

b. What properties of the soil influence the color of hydrangea flowers?

c. Do hydrangeas look more beautiful when grown in the right soil?

d. Was The Day After Tomorrow a better movie than Terminator?

e. Does grass require fertilizer in order to grow?

2. Read this hypothesis and answer the questions below:

Plants kept closer to windows grow larger than plants kept several feet away from windows.

a. Indicate the dependent variable:

b. Indicate the independent variable:

c. List 3 other variables that must be kept constant in this experiment (the control variables).

d. Write a prediction based on the above hypothesis.

Exercise 1.1

Take a Deep Breath

Students will need to take a picture of themselves or their group walking up and down on the step or doing other exercise. Include a note with your name and date on an index card in the picture. Insert picture here:

1. Identify the following in the experimental design. You will need to refer to the protocol to answer this question.

a. Independent variable:

b. Dependent variable:

c. Experimental dataset:

d. Control dataset:

e. Hypothesis:

2. Fill in the data for each individual in your group for the Breath experiment.

3. Look at the averages for all individuals in your group. Was the hypothesis you stated in the previous question supported by the “average data”? Explain your answer!!!

4. Now look at the data for each individual separately. Was there data for anyone in your group that did not support the hypothesis? If yes, explain whythis could be.

5. How many replicates did your group have?________________ Why is it good to have more than one replicate?

Exercise 1.2

Let’s Graph

In this exercise, you will be graphing the data that you collected in exercise 1.1.

1. In exercise 1.1, you identified the independent and dependent variables. Which one goes on the X axis of the graph and which goes on the Y axis?

2. Will you make a line or a bar graph of your data? Explain why you chose this type of graph.

3. You will need to use excel to generate a graph of your data. On this graph, you will need to label the title, independent variable, dependent variable and possibly the legend. You will need to select an appropriate scale so the data is spread out on the graph.

*Consult with your instructor to see how he/she would like for you to submit your graph. You might work on it in class and submit it through D2L or you might submit it at a different time. If you are taking the online version of the class, you will need to use Excel or word to make the graph.

Exercise 1.3

You will need to get the data under exercise 1.3 in the protocol sheet to complete these sections.

1. What is the dependent variable?

2. What is the independent variable?

3. Which, if any, of these individuals has diabetes? ___A or B ___?

4. What data do you have to support your hypothesis?

5. Construct a graph showing the time after eating each group had the greatest blood glucose levels.