Evaluating Information Flashcards

Question

What is the "Mean"?

Answer 1

The average

Answer 2

The middle value

Answer 3

The most common value

Answer 4

Sample size Mean Median Mode

Answer 5

Variance Standard Deviation Standard Error

Answer 6

can be viewed at the "spread" of data around a mean The average of the squared differences from the Mean

Answer 7

A statistic that tells you how tightly all the various examples are clustered around the mean in a set of data. When the examples are pretty tightly bunched together and the bell-shaped curve is steep, the standard deviation is small. When the examples are spread apart and the bell curve is relatively flat, that tells you you have a relatively large standard deviation.

Answer 8

Work out the Mean (average the numbers) The for each number subtract the Mean and then square the result (the squared difference) Then work out the average of those squared differences

Answer 9

To calculate Mean: 600+470+170+430+300 divided by 5 ("n" number of samples) = 394 mm To calculate the Variance: ``` subtract the Mean from the original heights 600-394 = 206 470-394 = 76 170-394 = -224 430-394 = 36 300-394 = -94 ``` ``` Square each of these and add them together then divide this number by the number of samples 206 squared is 42,236 76 squared is 5,776 -224 squared is 50,176 36 squared is 1,296 -94 squared is 8,836 ``` add them together the total is 108,520. Divide this by "n" the number of samples (5) to get the Variance 108,520/5 = 21,704 is the Variance To calculate Standard Deviation take the square root of the Variance: square root of 21,704 = 147.32 mm

Answer 10

Calculating Mean: doesn't change Calculating Sample Variance: When you have "n" data values that are a SAMPLE of the population you: divide by n-1 So in the previous example 108,520 is divided by 4 (n-1 or 5-1=4 ) to equal 27,130 Calculating Sample Standard Deviation: take the square of the Sample Variance = 164 mm

Answer 11

probabilities

Answer 12

Also called maintained hypothesis or research hypothesis. It states that there is a difference in our samples. An example might be where water quality in a stream has been observed over many years and a test is made of the null hypothesis that there is no change in quality between the first and second halves of the data against the alternative hypothesis that the quality is poorer in the second half of the record.

Answer 13

The Null Hypothesis is the opposite of the Alternative Hypothesis (H1). The null hypothesis (H0) is a hypothesis which the research tries to disprove, reject or nullify. It states that there is no change in our samples. H1 Hypothesis: Tomato plants exhibit a higher rate of growth when planted in compost rather than in soil. H0 Hypothesis: Tomato plants do not exhibit a higher rate of growth when planted in compost rather than soil.

Answer 14

A Null Hypothesis vs An Alternative Hypothesis. The Null Hypothesis means nothing will change the Alternative means there is a change.

Answer 15

The p-value (probability) is our chance of being wrong if we reject the null hypothesis and accept that our samples are significantly different. being wrong in this way is also called a Type I Error Higher p-values support the Null Hypothesis Lower P values support the Alternative Hypothesis

Answer 16

Type I - false positive Type II - false negative In statistical hypothesis testing, a type I error is the incorrect rejection of a true null hypothesis (a "false positive"), while a type II error is the failure to reject a false null hypothesis (a "false negative").

Answer 17

Higher p-values support the Null Hypothesis Lower p-values support the Alternative Hypothesis

Answer 18

a study design used to test cause-and-effect relationships between variables. The classic experimental design specifies an experimental group and a control group. The independent variable is administered to the experimental group and not to the control group, and both groups are measured on the same dependent variable