lesson 3

Question 1

whatre R groups

Answer 1

-need to mention groups when talking about tertiary structure
-determines interactions that happen to give protein tertiary shape
-what makes each amino acid unique

Question 2

what does students T-test measure

Answer 2

used to compare the means of 2 sets of data and decide if they’re statistically significantly different

Question 3

whatre the first steps of student T test (until squared standard deviations/number observations)

Answer 3

1)calculate mean for each data set
2)calculate the standard deviation for each dataset (s1 for standard deviation of sample 1 and s2 for standard deviation of sample 2)
3)square the standard deviations and divide by the number of observations in each sample (n1 and n2)

Question 4

What does the last step look like in the equation

Answer 4

s²1 s²2
—– —–
n1 n2

Question 5

Describe the next steps of student t test

Answer 5

4) add the products of step 3 together and find the square root
5)subtract the mean of sample 2 from the mean of sample 1 then divide this by the product of step 4

Question 6

What value do we get from step 5

Answer 6

The T value

Question 7

what do we need to compare the T value to?

Answer 7

find degrees of freedom of both samplesook at a table of t values and find which t value the degree of freedom calculated lies

Question 8

how do you calculate degrees of freedom (equation wont be provided)

Answer 8

number of individual measurements in a sample -1 (n1-1 + n2-1) =V

Question 9

part of equation for the difference between 2 means

Answer 9

_ _
X1 - X2

Question 10

whole equation (will be provided)

Answer 10

__ __
t= X1 - X2
——————-
√ s ²1 + s ²2
( —- —- )
n1 n2

Answer 11

calc mean of each dataset & subtract sample 2 from sample 1
find standard deviations for each dataset
square standard deviations of each dataset
divide by the number of individual measurements in each sample (separately form samples 1 and 2)
add these together then square root
divide difference of means by square root
thats the t value

find degrees of freedom, V (number if measurements in one sample-1, n1-1+n2-1)
see which value the degree of freedom relates to on a table comparing t values to degrees of freedom - critical valuesat right significance level (usually 5%)

t value>critical value means difference is likely signifdif and not due to chance- null hypothesis rejected

t value<critical value any difference is likely due to chance and not signif
The probability that any difference is due to chance is higher than 5 %
The null hypothesis is accepted