My Neers o Ask your Teacher 26 6803.3 points Previous Answers MintroStat8 2 E 51

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My Neers o Ask your Teacher 26 6803.3 points Previous Answers MintroStat8 2 E 511 XP. Iron-deficiency anemia is the most common form of malnutrition in developing countries, affecting about 50% of children and women and 25% of men. Iron pots for cooking foods had traditionally been used in many of these countries, but they have been largely replaced by aluminum pots, which are cheaper and lighter. Some research has suggested that food cooked in iron pots will contain more iron than food cooked in other types of pots. One study designed to investigate this issue compared the iron content of some Ethiopian foods cooked in aluminum, clay, and iron pots, One of the foods was yesiga wet, beef cut into small pieces and prepared with several Ethiopian spices. The iron content of four samples of yesiga wet cooked in each of the three types of pots is given below. The units are milligrams of iron per 100 grams of cooked food, data127.dat (a) Make a table giving the sample size, mean, and standard deviation for each type of pot. Is it reasonable to pool the variances? Note that with the small sample sizes in this experiment, we expect a e amount of variability n the sam ple standar deviations n s Type of pot Aluminum MOE (b) Run the analysis of variance. Report the F statistic with its degrees of freedom and P value. what do you conclude? (Round your test statistic to two decimal places. Round your P-value to three decimal places.) 27.58 P- 0.000 Conclusion: There is a statistically significant difference between the three treatment means at the a .05 level.

Explanation / Answer

we shall annswer this using the open source statisitical package R

The complete R snippet is as follows

typepot<- c("Aluminium","Aluminium","Aluminium","Aluminium","Clay","Clay","Clay","Clay","Iron","Iron","Iron","Iron")
g<- c("1","1","1","1","2","2","2","2","3","3","3","3")
iron <- c(2.05,1.99,1.65,2.1,1.7,2.04,2.3,2.13,4.98,3.65,5.78,4.09)

data.df <- cbind.data.frame(typepot,g,iron)

# perform anova analysis
a<- aov(lm(iron~ g*typepot,data=data.df))

#summarise the results
summary(a)

###########

The resulting anova table is as shown below

> summary(a)
Df Sum Sq Mean Sq F value Pr(>F)
g 2 18.463 9.232 27.58 0.000145 *** ## as the p value is less than 0.05 , hence we can safely conclude that the value of the iron content varies across different groups.
Residuals 9 3.012 0.335   
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Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

However , as we do not see any interaction effect in the data , hence it is evident that there is no iteraction between the 2 independent variables type pot and g .

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