Flashcards in Lab 1: Data Analysis and presentation Deck (20):

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## RAW DATA

### Large quantities of data collected when conducting field studies or experiments

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## SUMMARY STATISTICS/DESCRIPTIVE STATISTICS

### presentation of data that give an overview of trends in a manner the reader can understand

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## Commonly reported statistics include

###
1. mean : average

2. minimum values

3. maximum values

4. range

5. standard deviation

6. standard error

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## STATISTICS

### a feild of study that provides quantitative tools for summarizing data and testing hypotheses

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## VARIANCE

### spread of data around the mean

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## STANDARD DEVIATION

### measures the variance ( the spread of data around the mean)

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## mean +/- 1 SD

### The value encompasses approx 68% of the dat point in a data set

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## mean +/- 2 SD

### The value encompasses approx 98% of the dat point in a data set

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## STANDARD ERROR

### It is the measure of how certain we are that a calculated mean is reliable

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## STANDARD DEVIATION

### measures the variance ( the spread of data around the mean)

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## mean +/- 1 SD

### The value encompasses approx 68% of the dat point in a data set

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## mean +/- 2 SD

### The value encompasses approx 98% of the dat point in a data set

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## INFERENCES

### reach conclusions about a species or population based on samples of a few individuals

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## NULL HYPOTHESES

### That the mean masses of two populations are equal

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## PROBABILITY VALUE, P values

### which is the probability or likelihood the null hypotheses is true

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## P-VALUE ranges

### 0.00 - 1.00

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## The standard P-value for judging whether a null hypotheses is accepted or rejected

###
.05

< .05 is rejected

> .05 is accepted

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## ANOVA ( Analysis of variance

### commonly used to compare 3 or more means rather than 2 means

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## REGRESSION ANALYSIS

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a means of determining whether a significant linear relationship exist between 2 or more variables

. It generates the slope of the line fitted to data points , and then tested to see if the slope deviates significantly from zero

Y=AX + B

. If the coefficient (A) slope is positive the relationship between the dependent variable and independent is a direct one and line slopes upward.

.If the regression coefficient is negative : the relationship is inverse and lines slope downwards

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