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

1. The risk of acquiring disease is measured by the a. Incidence rate b. Incidence rate times the average duration of the disease c. Incidence rate divided by the prevalence rate d. Prevalence rate e. Prevalence rate times the average duration of the disease

2. The strength of an association between a factor and a disease is best measure by a. Incubation rate b. Incidence of the disease in the total population c. Prevalence of the factor d. Attributable risk e. Relative risk

3. Case fatality rate for a given disease refers to a. The crude mortality rate per 100,000 population b. Cause-specific mortality rate due to the disease c. A fatal outcome of any disease d. The percentage of deaths among cases of the disease e. The proportion of deaths due to the disease among all deaths from all causes

4. An investigator is interested in etiology of neonatal jaundice. To study this condition, he selected 100 children who were diagnosed with this condition and 100 children born in the same period and in the same hospital who did not have a diagnosis of neonatal jaundice. He then reviewed the obstetrical and delivery records of their mothers to determine various prenatal and perinatal exposures. This is an example of a(n): a. Cross-sectional study b. Case-control study c. Cohort study d. Clinical trial e. Experiment

5. Which of the following statements describes the major advantages of a randomized clinical trial? a. It avoids observer bias b. It lends itself to ethical justification c. It yields results replicable in other patients d. It rules out self-selection of participants to the different treatment groups d. It enrolls representative patients

6. A survey conducted in England revealed that of 224 families in which there had been a known case of poliomyelitis, 56 maintained parakeets as a family pet. In another British survey, 30 out of 99 poliomyelitis patients questioned kept parakeets. The inference that there is some relationship between the presence of a parakeet in a household and the occurrence of poliomyelitis among household members is a. Correct b. Incorrect because of failure to distinguish between incidence and prevalence c. Incorrect because a proportionate ratio is used when a rate is required to support the inference d. Incorrect because a failure to recognize a possible cohort phenomenon e. Incorrect because there is no control or comparison group.

7. An investigator determines the correlation coefficient between triglyceride levels and degree of atherosclerosis in sampled blood vessels to be +1.67. On the basis of this you would conclude that: a. Triglyceride level is a good predictor of atherosclerosis b. Triglyceride level is not a good predictor of atherosclerosis c. High triglyceride levels cause atherosclerosis d. Atherosclerosis cause high triglyceride levels e. The investigator has incorrectly determined the correlation coefficient

8. A screening test of known sensitivity and specificity is applied to two populations. The prevalence of the disease being screened for is 10% in population A and is 1% in population B. Which of the following is true? a. The percent of all negative tests that have false-negative results is lower in population A than in population B. b. Specificity is lower in population A than in population B. c. Reliability is higher in population A than in population B. d. The percent of all positive tests that have false-positive results is lower in population A than in population B. e. Specificity is higher in population A than in population B.

9. Serum cholesterol levels are obtained for four healthy men. The probability that all will fall below the 10th percentile of the distribution of cholesterol for healthy males is: a. 0.4 b. 1 â (0.1)4 c. (0.1)4 d. (0.9)4 e. Cannot be determined from these data

10. In a diabetes screening program, the screening level for a positive blood sugar level in test 1 is set at 160 mg/dl, and in test 2 at 130 mg/dl. The sensitivity is: a. Greater in test 1 b. Greater in test 2 c. Equal in test 1 and 2 d. Dependent on the size of the population being evaluated

Part II 1.The California Occupational Mortality study data set was employed to assess mortality data for the years 1979-1981. A 2% sample of employed persons from the 1980 census of California was used. It contains the occupation of each person who had died. This study, like any occupation-based study, is restricted to the work life span as far as age of subjects is concerned. This study used ages 16-64 years. Certain persons, because of their source of work, were excluded as subjects: homemakers, retired persons, students, disabled, military personnel, etc. Only main-stream-type employment was used in this study to establish occupations at risk for heavy alcohol drinking. Using the Table below, answer the following:

1.What occupations are most vulnerable to acquiring cirrhosis of the liver from heavy drinking?

2.List several of the occupations identified by the research studies that are more vulnerable to alcohol-induced, cirrhosis related deaths and that have the highest mortality rates.

3. What are possible confounding variables for the research in occupations and heavy drinking that lead to fatal diseases?

4. Based on available research data, develop and construct a web of causation along with the appropriate decision trees for occupational group-related alcohol deaths. Table. Alcohol Related Deaths in California, 1979-1981 Cirrhosis 5.5% Digestive organ cancers 5.7% Injuries 13.7% Suicide and homicide 5.% All other causes 64.9%

Zika and microcephaly Since May 2015, Brazil has experienced a significant outbreak of Zika virus. In recent years, Brazilian officials reported an increase in the number of babies born with microcephaly.

1. Briefly describe what we know and what we do not know about Zika virus.

2. What has been done and what should be done to prevent Zika virus epidemic in US and world-wide?

Part II 1.The California Occupational Mortality study data set was employed to assess mortality data for the years 1979-1981. A 2% sample of employed persons from the 1980 census of California was used. It contains the occupation of each person who had died. This study, like any occupation-based study, is restricted to the work life span as far as age of subjects is concerned. This study used ages 16-64 years. Certain persons, because of their source of work, were excluded as subjects: homemakers, retired persons, students, disabled, military personnel, etc. Only main-stream-type employment was used in this study to establish occupations at risk for heavy alcohol drinking. Using the Table below, answer the following:

1.What occupations are most vulnerable to acquiring cirrhosis of the liver from heavy drinking?

2.List several of the occupations identified by the research studies that are more vulnerable to alcohol-induced, cirrhosis related deaths and that have the highest mortality rates.

3. What are possible confounding variables for the research in occupations and heavy drinking that lead to fatal diseases?

4. Based on available research data, develop and construct a web of causation along with the appropriate decision trees for occupational group-related alcohol deaths.

Table. Alcohol Related Deaths in California, 1979-1981 Cirrhosis 5.5% Digestive organ cancers 5.7% Injuries 13.7% Suicide and homicide 5.% All other causes 64.9% 2. Zika and microcephaly Since May 2015,

Brazil has experienced a significant outbreak of Zika virus. In recent years, Brazilian officials reported an increase in the number of babies born with microcephaly.

1. Briefly describe what we know and what we do not know about Zika virus.

2. What has been done and what should be done to prevent Zika virus epidemic in US and world-wide?

Multiple Choice

5. Which of the following statements describes the major advantages of a randomized clinical trial? a. It avoids observer bias b. It lends itself to ethical justification c. It yields results replicable in other patients d. It rules out self-selection of participants to the different treatment groups d. It enrolls representative patients

6. A survey conducted in England revealed that of 224 families in which there had been a known case of poliomyelitis, 56 maintained parakeets as a family pet. In another British survey, 30 out of 99 poliomyelitis patients questioned kept parakeets. The inference that there is some relationship between the presence of a parakeet in a household and the occurrence of poliomyelitis among household members is a. Correct b. Incorrect because of failure to distinguish between incidence and prevalence c. Incorrect because a proportionate ratio is used when a rate is required to support the inference d. Incorrect because a failure to recognize a possible cohort phenomenon e. Incorrect because there is no control or comparison group.

7. An investigator determines the correlation coefficient between triglyceride levels and degree of atherosclerosis in sampled blood vessels to be +1.67. On the basis of this you would conclude that: a. Triglyceride level is a good predictor of atherosclerosis b. Triglyceride level is not a good predictor of atherosclerosis c. High triglyceride levels cause atherosclerosis d. Atherosclerosis cause high triglyceride levels e. The investigator has incorrectly determined the correlation coefficient

8. A screening test of known sensitivity and specificity is applied to two populations. The prevalence of the disease being screened for is 10% in population A and is 1% in population B. Which of the following is true? a. The percent of all negative tests that have false-negative results is lower in population A than in population B. b. Specificity is lower in population A than in population B. c. Reliability is higher in population A than in population B. d. The percent of all positive tests that have false-positive results is lower in population A than in population B. e. Specificity is higher in population A than in population B.

9. Serum cholesterol levels are obtained for four healthy men. The probability that all will fall below the 10th percentile of the distribution of cholesterol for healthy males is: a. 0.4 b. 1 â (0.1)4 c. (0.1)4 d. (0.9)4 e. Cannot be determined from these data

10. In a diabetes screening program, the screening level for a positive blood sugar level in test 1 is set at 160 mg/dl, and in test 2 at 130 mg/dl. The sensitivity is: a. Greater in test 1 b. Greater in test 2 c. Equal in test 1 and 2 d. Dependent on the size of the population being evaluated

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