Statistical tests
Chi squared test
- Used to test the null hypothesis → that there will be no statistically
significant difference between any observations and that any differences are due to
chance.
- Examine observed vs expected results
- Using categorical data
Criteria for the test:
- Large (20+) sample size
- Data must be discrete
- Only raw counts can be used, no percentages etc
- Used to compare experimental results with theoretical ones e.g genetic crosses
- Can't use negative data, so can’t tell whether one group is higher or lower than the
other.
Degrees of freedom → number of categories - 1
Given a table and have to match up the degrees of freedom and then can see if P>0.05
Calculations:
So x2 = 1
, - Chi squared can be used in genetics e.g in dihybrid crosses
Critical values → cut-off values that define regions where the test statistic is
unlikely to lie
P-value → In null-hypothesis significance testing, is the probability of obtaining
test results at least as extreme as the result actually observed, under the
assumption that the null hypothesis is correct. P>0.05 null hypothesis is true.
Standard deviation
- Only works for normal distribution curves
Measures proportion of data and how it’s dispersed each side of the mean
68% of all measurements lie within the +1.0 standard deviation
95% of all measurements lie within +2.0
Chi squared test
- Used to test the null hypothesis → that there will be no statistically
significant difference between any observations and that any differences are due to
chance.
- Examine observed vs expected results
- Using categorical data
Criteria for the test:
- Large (20+) sample size
- Data must be discrete
- Only raw counts can be used, no percentages etc
- Used to compare experimental results with theoretical ones e.g genetic crosses
- Can't use negative data, so can’t tell whether one group is higher or lower than the
other.
Degrees of freedom → number of categories - 1
Given a table and have to match up the degrees of freedom and then can see if P>0.05
Calculations:
So x2 = 1
, - Chi squared can be used in genetics e.g in dihybrid crosses
Critical values → cut-off values that define regions where the test statistic is
unlikely to lie
P-value → In null-hypothesis significance testing, is the probability of obtaining
test results at least as extreme as the result actually observed, under the
assumption that the null hypothesis is correct. P>0.05 null hypothesis is true.
Standard deviation
- Only works for normal distribution curves
Measures proportion of data and how it’s dispersed each side of the mean
68% of all measurements lie within the +1.0 standard deviation
95% of all measurements lie within +2.0
