Searching literature and statistics

Question 1

Strategies for reading research articles

Answer 1

1. Read abstract
2. Read discussion
3. Read methodology
4. Take notes, read 2-3 times, look up definitions as you read

Question 2

Statistics definition

Answer 2

The methodology for collecting, analyzing, interpreting, and drawing conclusions from data

Question 3

Data

Answer 3

facts that can be analyzed or used in an effort to gain knowledge or make decisions; info

Question 4

Statistics provides methods for:

Answer 4

Design- planning and carrying out research
Description- summarizing/ exploring data
Inference- make prediction and generalize about phenomena represented by the data

Question 5

Why should we care about statistics?

Answer 5

To be able to effectively conduct research- gives us a tool to use such that researchers can consistently analyze data- unbiased and accurate- honest, reliable
To be able to read and evaluate journal articles- statistics often show us both the questions and the answers to those questions
To further develop critical thinking and analytic skills
To act as an informed consumer

Question 6

Variable

Answer 6

A characteristic, #, or quantity that incr or decr. Over time, or
takes different values in different situations; a factor in a scientific experiment that may be subject to change

Question 7

Quantitative

Answer 7

numerical- can be counted/ measured

Question 8

Qualitative

Answer 8

you can’t measure it- the quality- color, categories, etc

Question 9

Descriptive stats

Answer 9

For organizing and studying data- graphs, charts, tables, averages, measures of variation, percentiles
Ex: Arithmetic mean: sum of a collection of #s divided by # of #s
Standard deviation: measure of spread of #s in a set of data from its mean value
Derived from sample variance

Question 10

Why must we consider the standard deviation when comparing group means?

Answer 10

Two groups of data with the same mean may have very different standard deviations (spread of values- used to determine how much the mean accurately represents the data set)

Question 11

Significance test

Answer 11

a method of inference used to support/ reject claims based on sample data

Question 12

Null hypothesis

Answer 12

(H sub 0): no observed difference between experimental groups

Question 13

Alternative hypothesis

Answer 13

(H sub A): there will be an observed difference between experimental groups

Question 14

Statistical significance

Answer 14

a result is unlikely to have occurred by chance alone, and is determined by a p-value

Question 15

P-value

Answer 15

an estimate of the probability that a particular result could have occurred by chance, assuming the null hypothesis is true

Question 16

Analyzing the p-value

Answer 16

Ex: the probability of being wrong if you reject the null hypothesis, or the probability of finding a difference when there is no real difference
If the p-value is small, there is a low probability that you will be wrong if you reject the null hypothesis and accept the alternative
Estimate of the probability that a result was determined by chance- if the p-value is small, it is more likely that the results were not due to chance, and therefore actually significant to the experiment

Question 17

Predictor variables

Answer 17

independent- variable that is being studied or manipulated in order to measure the result in the response variable

Question 18

Response variables

Answer 18

dependent

Question 19

Linear regression

Answer 19

statistical analysis assessing the association between 2 continuous variables

Question 20

Example of linear regression:

Answer 20

can we predict body weight based on a person’s height
Null: slope of the data = 0
Alternative: slope doesn’t = 0- has either a positive or negative relationship

Question 21

T-test

Answer 21

used to determine if 2 variables are significantly different from one another

Question 22

Example of t-test

Answer 22

does insecticide treatment (categorical predictor variable) reduce insect damage (continuous response variable) to plants?
Null: no diff in the mean values between 2 samples
Alt: means are different- the treatment is reducing insect damage

Question 23

Chi-square

Answer 23

used to determine whether there is a significant association between 2 categorical variables

Question 24

Example of chi-square

Answer 24

Ex: are white and gray moths eaten equally by birds? The predictor variable is moth color (white or gray; categorical) and the response variable is mortality (dead or alive; categorical)
Null- variable A and B are independent
Alternative- variable A and B are NOT independent