BIO 305 Lecture Notes - Lecture 3: Null Hypothesis, Analysis Of Variance

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cyanherring316

27 Jan 2020

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Continuation from lecture 1 standard deviations and standard error doesn"t need to be by hand because r will do it for you. When t value is all by itself it doesn"t mean anything so compare to a critical value. For the combination of sample sizes that we have what is the probability that the null hypothesis is incorrect. Some value that corresponds to the value that the null hypothesis is rejected and whether or not it is less than alpha. Alpha is a standard set ahead of time normally set at 0. 05. Willing to accept a 5% chance that there actually is not a difference when it looks like there is. Doesn"t necessarily have to be set at 0. 05 but it is absolutely set ahead of time. If the value is less than 0. 05 then we can say that the null hypothesis is not true. What happens if n is less than 8.

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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?

To determine if our data is consistent with expected results.
		a To determine if our data is consistent with expected results. b To determine if our data exactly matches the expected results.
		c To determine the expected results.
	d	To compare the phenotypic ratios to the genotypic ratios.

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= ___.

	a.	2.22
	b	2.71
	c	4.36
	d	187.78
	e	448.27

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

a.		Fail to reject the null
b.		Reject the null
c.		It cannot be determined from the data given

silversalmon27

Read the following passage focusing your attention on the scientific procedures and scientific abilities illustrated in it. Think about what types of experiments (observation, testing or application) are described. Identify the hypothesis, predictions, outcomes of experiments and assumptions that appear in the passage. The standard explanation of how humans originally acquired AIDS is that HIV (human immunodeficiency virus) originally was transmitted to humans from monkeys or apes carrying SIV, simian immunodeficiency virus. How could the transmission have occurred? Several similar hypotheses involve an African hunter coming in contact with monkey blood. For example this could have occurred when a hunter butchering a monkey, got some of its blood in a cut, or when a human ate undercooked monkey meat, or when a monkey bit a human. Depending on one's assessment of the genetic diversity of HIV over time, this transmission might have occurred only a few decades ago or, alternatively, hundreds or thousands of years ago. If the latter is correct then AIDS could have been restricted to remote African villages until recent decades when trade and international travel led to the current pandemic. There are however other alternative explanations for the spread of AIDS. One of them is that AIDS arose from contaminated polio vaccines used in Africa from 1957-59. Why is this a plausible explanation? Polio vaccines are cultured on apesâ kidneys, so contamination of a batch of vaccine by an SIV is a possibility. There is a precedent: in the 1950s and early 1960s millions of doses of polio vaccine were contaminated by another simian virus, SV-40. The vaccine alleged to be the origin of AIDS was given to hundreds of thousands of people in central and west Africa from 1957-1959. These locations later had some of the world's highest levels of HIV infection. The timing is also right, since the earliest known cases of AIDS date from the 1960s; the earliest HIV-positive blood sample was collected in Kinshasa in 1959. At the time, there was no way of testing for the presence of SIVs, which were only discovered in the 1980s. Another factor adds plausibility to the theory: the vaccine was given to many infants less than a month old, in an extra high dose. Since the immune systems of infants are not fully developed, this is an excellent way to help a virus jump the species barrier. Some scientists argue that the above explanation is not necessarily correct but that it is worth taking seriously. There are a number of ways to test it. One is to analyze stocks of polio vaccine; if the explanation is correct, then it is probable that some of the vaccines will carry SIV. Another is to scrutinize records of early polio vaccination campaigns in Africa. If it is true that the immunodeficiency virus passed to humans by way of those vaccines, the areas where the campaigns took place would be the same as those where the initial sprouts of the disease occurred and where the larger number of cases occurred during the early stages of the pandemic. Another is to analyze blood samples in Africa from the 1950s and earlier (pre polio vaccination): if the immunodeficiency virus was transmitted via the polio vaccine, HIV should not be found. Adapted from âPolitical refutation of a scientific theory: the case of polio vaccines and the origin of AIDSâ. Brian Martin, published in Health Care Analysis, Vol. 6, 1998, pp. 175-179. Now reread the passage and answer the following questions.

5. For each experiment, write an outcome that would disprove the hypothesis of AIDS passing from monkeys to humans through polio vaccines.

6. What outcomes of the experiments would fail to disprove the hypothesis of AIDS passing from monkeys to humans through polio vaccines?explain.

7.What outcomes would prove the hypothesis? Hint: This is not the same as question 6. Think about what would you need to do to 100% prove a hypothesis.

8. For what reasons do scientists need to conduct testing experiments?

ochrejackal75

Comments on this, i need a paragrapgh on comments abaout this...

Abortion keeps being a controversy because both sides of the spectrum have valid points. The side that is prolife it right about abortion being the termination of an organism. Their believe system states that murdering human being is wrong and since an unborn child is still a human child, then by default this should be condemned as a wrong thing. They also say they are helping the woman themselves because abortion can have âthe risk of breast cancer in those who had experienced an induced abortion was 50% higher than among other womenâ however the same study states âthe results across all epidemiologic studies of this premise are inconsistentâboth overall and within specific subgroups. The risk of breast cancer should be re-examinedâ. This means we should not jump in to conclusion because more studies need to be done before accepting something as fact. The side for pro-choice states that a woman should have the choice to make her own decision no matter if it is a good or bad decision. A decision that will change her live completely and most of the time make it harder for a woman to get ahead in life.

I am pro-choice, not because I like terminating live, I am actually pro-live of any type of organisms not just humans, but because woman who phase this problem should have their reason or really are not prepare to have a baby in a modern society, and as Mack T Brown said âThe value of a self-represented future resides within the person herself, as a feature of a richly complex mental life". Both sides of the argument go to the extreme to explain their case pro-choice and give the example of a raped woman. Pro-live give the example of that a baby is always a good thing. Both acceptable, however most woman are not in this spectrums, an example that is more relevant is a woman who does not have the emotionally and or financial maturity to make the choice that is to have a child. Physically a girl is ready to have a child when her menstrual cycle begins that is usually around 13. Most people would agree that a girl of that age will not have any type of maturity to take care of even herself less a child. Letâs not go far letâs say a girl of eighteen years old getting out of high school, she may have a rare emotional maturity at that age to have the child but in todayâs society impossible without any help from family members to take care of that child. How many hours will she work? How will she take care of the child? How will she go to school to better herself for the future to come? These girls that are asking themselves if they should have an abortion is not because it is something they would like to do, it is a hard decision to postpone taking that live changing decision before they are ready to do it and not be a burden in society.

The current abortion law is strict, so abuse of the law will be very hard to do. In the third trimester a woman would need 2 signatures of two physicians to be able to do an abortion. I personally think that this is great this way we can assure that there is no negligence from any party. The part of the law I do not agree with is that the law says that if during the abortion the baby is born alive they need to offer emergency services. This defeats the purpose of an abortion that as harsh as it sounds it is to terminate the pregnancy cycle before time.

BIO 305 Lecture Notes - Lecture 3: Null Hypothesis, Analysis Of Variance

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