Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

MST2101 > EXAM stuff > Flashcards

EXAM stuff Flashcards

1
Q

What is chi square

A
  • Test for association or randomness or homogeneity
  • Non-parametric test to compare observed results to expected results on the basis of a null hypothesis
  • Samples must be random
  • Expected frequency must exceed 5
  • Calculates a c²-statistic that is compared to a statistical table to determine whether there is a statistically significant difference between the observed and expected frequencies
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Null hypothesis for chi squatred

A

There was no significant difference in observed and expected values for L. obtusata of each colour

OR

There was no significant difference in frequency of occurrence between the three colours

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

t tests

A
  • Parametric test to compare the means of two sets of continuous data
  • Can be used with large and small sample sizes
  • Calculates a t-statistic and P-value that allow us to determine whether there is a statistically significant difference in the two means
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

data screening t test

A
  • Data must be continuous
  • i.e. measurements or on an uninterrupted scale
  • Data should be normally distributed
  • Use plot or normality test (e.g. Kolmogorov Smirnov)
  • Variances should be similar between samples
  • Use F-test for equality of variance
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

p vlalue t test

A
  • If your P-value is less than 0.05 then there is a statistically significant difference in the means (at P = 0.05) and we can reject a null hypothesis
  • If your P-value is greater than 0.05 then there is no statistically significant difference in the means (at P = 0.05) and we can accept a null hypothesis
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

what is a mann-whitney u test?

A
  • Non-parametric test to compare the medians of two sets of discontinuous data
  • Can be used with as few as 4 observations in each sample
  • Samples can be unequal
  • Distribution free so can be used with non-normal data
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

p value mann whitney u

A
  • If your P-value is less than 0.05 then there is a statistically significant difference in the medians (at P = 0.05) and we can reject a null hypothesis
  • If your P-value is greater than 0.05 then there is no statistically significant difference in the medians (at P = 0.05) and we can accept a null hypothesis
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

what is an anova?

A
  • One-way analysis of variance
  • Parametric test to compare the means of three or more sets of data
  • Samples can be unequal
  • Calculates a F-statistic and a P-value that allow us to determine whether there is a statistically significant difference between the three (or more) means
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

p value anova

A
  • We determine significance using the P-value
  • If your P-value is less than 0.05 then there is a statistically significant difference in the means (at P = 0.05) and we can reject a null hypothesis
  • If your P-value is greater than 0.05 then there is no statistically significant difference in the means (at P = 0.05) and we can accept a null hypothesis
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

what is a krustal wallace?

A
  • Non-parametric test to compare the medians of three or more sets of data
  • Can be used with as few as 5 observations in each sample
  • Samples can be unequal
  • Distribution free so can be used with non-normal data
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

krustal wallace p value

A
  • We determine significance using the P-value
  • If your P-value is less than 0.05 then there is a statistically significant difference in the medians (at P = 0.05) and we can reject a null hypothesis
  • If your P-value is greater than 0.05 then there is no statistically significant difference in the medians (at P = 0.05) and we can accept a null hypothesis
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What do corralations establish?

A
  • Need to establish
  • If there is a relationship
  • Nature of the relationship
  • If relationship is significant
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is a pearsons corralation coefficient?

A

•Also called Product Moment Correlation Coefficient

•

•Parametric test to determine if there is a linear relationship between two variables

•

•Calculates a r-statistic and a P-value that allow us to determine whether there is a statistically significant relationship between two variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

p vlaue pearsons corralation coefficient

A
  • If your P-value is less than 0.05 then there is a statistically significant relationship between the two variables (at P = 0.05) and we can reject a null hypothesis
  • If your P-value is greater than 0.05 then there is no statistically significant relationship between the two variables (at P = 0.05) and we can accept a null hypothesis
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

what is a spearmens rank corralation coefficient?

A

•Non-parametric test to determine if there is a relationship between two variables

•

•Use if both variables or one variable is discontinuous

•

•Converts x and y variables into ranks

•

•Calculates a rs-statistic and a P-value that allow us to determine whether there is a statistically significant relationship between two variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

spearmens rank p value

A
  • If your P-value is less than 0.05 then there is a statistically significant relationship between the two variables (at P = 0.05) and we can reject a null hypothesis
  • If your P-value is greater than 0.05 then there is no statistically significant relationship between the two variables (at P = 0.05) and we can accept a null hypothesis
17
Q

mean median mode

A
  • MEAN - sum of a set of observations divided by number of observations
  • MEDIAN - middle value of a ranked set of data
  • MODE - value occurring most frequently
18
Q

Three main measures of variability:

A

•STANDARD DEVIATION - calculated from all observations

  • standard degree of variability around the mean

•RANGE - highest and lowest observation

  • reported with median

•VARIANCE - square of the standard deviation

19
Q

How to measure standard deviation

A
  1. Subtract the mean from each of your numbers in your sample.
  2. Square all of the numbers from each of the subtractions you just did.
  3. Add the squared numbers together.
  4. Divide the sum of squares by (n-1). - varience
  5. Take the square root of the variance. - standard deviation
20
Q

Was there any significant difference between the high fertilisation dose (HF) and extra-high fertilisation dose (XF) for both the low marsh and the high marsh?

A

There was no significant difference in accretion rates between the HF and XF treatments for either the low marsh (ANOVA, F = 1.5, df = 2, P = 0.35) or the high marsh (ANOVA, F = 4.58, df = 2, P = 0.12).

21
Q

There was no significant difference in accretion rates between the HF and XF treatments for either the low marsh (ANOVA, F = 1.5, df = 2, P = 0.35) or the high marsh (ANOVA, F = 4.58, df = 2, P = 0.12).

A

Current data is similar to Turner’s data for the control treatment in the low marsh though is slightly lower in the high marsh compared to the previous data.

For the HF treatment, the accretion values for both the high marsh and the low marsh were similar to the data from the previous study.

The major difference occurred for the XF treatment in the low marsh, with much lower accretion rates compared to Turner’s data.

22
Q

How did fertilisation of the low marsh compare to fertilisation of the high marsh?

A

Fertilisation in the high marsh was initially at a higher level than the low marsh for both the HF (4% compared to 1%) and the XF treatment (5.5% compared to 3%). This trend continued from 1970 to 2010 with the high marsh displaying higher d15N over the study period than the low marsh.

23
Q

Fertilisation in the high marsh was initially at a higher level than the low marsh for both the HF (4% compared to 1%) and the XF treatment (5.5% compared to 3%). This trend continued from 1970 to 2010 with the high marsh displaying higher d15N over the study period than the low marsh.

A

The d15N values in the fertilised treatments were much higher compared to the control. All fertilised treatments displayed a strong positive relationship between time and d15N. This relationship was not as strong for the control treatments.

24
Q

Determine the average and within sample variability in the number of shoots in each area for each treatment.

Suggest what your findings show about the effect of fertilisation on vegetation abundance in both the low marsh and the high marsh.

A

Overall, the abundance of Spartina shoots was much higher in the high marsh compared to the low marsh. Within the low marsh, the XF treatment had the greatest abundance of shoots (median = 8.5 ± 19 range) compared to the HF treatment (median = 5.5 ± 11 range) with the control having the lowest abundance (median = 2.5 ± 9 range).

For the high marsh, the same pattern was observed with the XF treatment displaying the greatest abundance of vegetation (median = 17.5 ± 14 range), followed by the HF treatment (median = 26.5 ± 7 range) with the control treatment displaying the lowest abundance (median = 7 ± 7 range).

MST2101 (25 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions