Data Analysis

Question 1

Def of correlation

Answer 1

A change in one variable is associated with a change in the other variable

Question 2

Def of causation

Answer 2

A change in one variable is responsible for a change in the other variable

Question 3

Def of standard deviation

Answer 3

The spread of data around the mean value
(shown as error bars on graphs)

Question 4

When are results precise/ precision

Answer 4

Good precision means the result can be reproduced/repeated
This means little variability between repeats when experiments are repeated

Question 5

When is data unreliable (not precise)?

Answer 5

If graph fluctuates up and down
If repeats are far away from the mean (large error bars)

Question 6

Advantage of large sample size

Answer 6

-allows you to identify anomalies
- allows you to calculate a more reliable mean
- allows you to reduce the effect of anomalies on the mean

Question 7

Precision of measurements means….

Answer 7

How sensitive the instrument is
(I.e how small are the increments that can be measured)

Question 8

For valid methodology consider..

Answer 8

• comparing like to like
  This ensures that there is no factor that may affect the results
• factors that might affect the outcome need to be controlled
  If factor cannot be controlled it should be monitored

Question 9

For a valid comparisons you must

Answer 9

• compare two numbers directly
  If the numbers are not equal then comparing the % can lead to valid comparisons

Question 10

How do you prevent bias

Answer 10

Selecting patients/ sample sires randomly

Question 11

Def of Accuracy
+ what do you need for accurate data?

Answer 11

The results are close to the ‘real value’

Requires
+ valid test, reliable data and precise measurements
+ no errors and no bias

Question 12

When evaluating if data supports conclusion include:

Answer 12

• are organisms tested same as conclusion?
• is sample size large
• is the test bias
• are there statistical tests
• how large are error bars
• control variables controlled?

Question 13

What is normal distribution?

Answer 13

Plotting data to get a smooth symmetrical curve that peaks in the middle
(this peak where most data was collected is the normal distribution with extremes on either side.)

Question 14

What is needed for test it be statistically significant?

Answer 14

• need to be 95% confident that the results are not due to chance
  We can never be 100% confident as biological systems show variation and on any day results may be different

Question 15

Equation of standard deviation

Answer 15

————-
/ ∑(x-x̅)^2.
/. ————- = S
\—. N - 1

N= total number of values
X = each individual value
x̅ = mean
S = standard deviation (SD)

Question 16

What is null hypothesis?

+ how do you confirm results with it?

Answer 16

This is always opposite to hypothesis and negative states that
no significant difference or association between the two samples it assumes that difference occurs due to change.

+ a statistical test will tell you wether you can accept or reject this null hypothesis
Accepting = no significant difference between results
Rejecting = significant difference between results

Question 17

Conclusion if rejecting the null hypothesis

Answer 17

The null hypothesis is rejected. There is a significant difference between the mean values (be specific here). There is a less that 5 % probability that these results are due to chance.

Question 18

Conclusion if accepting the null hypothesis

Answer 18

The null hypothesis is accepted. There is no significant difference between the mean values (be specific here). There is a more that 5 % probability that these results are due to chance.

Question 19

Practice Calc of standard deviation

Answer 19

See notes

Question 20

What is Chi-Squared test for

Answer 20

Establishing whether the difference between observed and expected results is small enough to occur purely due to change.

It can be used to test the null hypothesis

Question 21

What is the criteria for a Chi-Squared test

Answer 21

1- Sample size must large enough (over 20)
2- use data that falls into discrete categories
3- only raw counts and not percentages or rates can be used
4- observed data and expected needed

Question 22

Formula for chi-squared Test

Answer 22

X2 =