Ecological Data Analysis

Ecological Data Analysis - Ecological Data Analysis Mrs....

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Ecological Data Analysis Yes, it’s all in your lab manual! Mrs. Crerar Ecology 307 - Laboratory
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The Scientific Method Make Observations Can be qualitative (words) or quantitative (numbers) p. 24
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The Scientific Method Formulate Hypotheses Propose an explanation for your observations Develop Test Hypotheses Design an experiment including variables and controls Revise Hypotheses Do not prove…SUPPORT Communicate Conclusions Report your data in an objective manner, but REPORT!! p. 24
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Ecological Sampling Statistical population Estimate a characteristic of a large group by measuring just a small subset of that group. Sample population A subset of the true or statistical population. Bias Some of the members in a population are selected more often than expected by chance. p. 25
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Frequency Distribution Graphing is the first step in analyzing data. Distribution can be skewed or normal. p. 25
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Descriptive Statistics Measures of Central Tendency Mean: an average of all values Median: the value in the middle of the list. If the list has an even number of values, average the two in the middle Mode: the value that occurs the most often N N N N i i X X X X X X ... 3 2 1 1 + + = = = p. 28
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Descriptive Statistics Measures of Dispersion Range: difference between largest and smallest data point Sample data: 4, 17, 10, 27, 3, 52, 64, 2, 3, 5, 24, 27, 18, 3, 65 Mean: Median: Mode: Range: 21.6 p. 28 2, 3, 3, 3, 4, 5,10, 17 , 18, 24, 27, 27, 52, 64, 65 3 65 – 2 = 63
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Descriptive Statistics Measures of Dispersion Variance: information on the distribution of data around the mean ( 29 1 N 1 2 2 - - = = N i i X X S p. 28 Similar to the idea of distance, variance is always positive. Variance measures the density or spread of the data.
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Variance Table 1. Sample calculations for variance (S 2 ) in the height of oak trees Height (m) X i – X ( X i – X ) 2 28.8 9.8 96.04 12.9 -6.1 37.21 25.0 6.0 36.00 11.8 -7.2 51.84 16.5 -2.5 6.25 Mean = SS x = N = df = N – 1 = S 2 = 19.0 m 227.3 5 p. 29 variance 4
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Variance = 227.3 = 56.8m² p. 29 1 N 2 - = SSx S 4
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Standard Deviation 1 SS S x 2 - = N ( X i – X ) 2 96.04 37.21 36.00 51.84 6.25 SS x = 227.3 p. 29 = 56.8 m 2 2 S = S variance standard deviation Standard Deviation is used to show variation around a value. It is also reported as ±. It can also change the units of variance. = 7.5 m
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Variance Table 1. Sample calculations for variance (S 2 ) in the height of oak trees Height (m) X i – X ( X i – X ) 2 28.8 9.8 96.04 12.9 -6.1 37.21 25.0 6.0 36.00 11.8 -7.2 51.84 16.5 -2.5 6.25 Mean = SS x = N = S 2 = 19.0 m 227.3 5 p. 29 56.8 m 2 S = + 7.5 m
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Inferential Statistics Assumptions of Parametric and Non-parametric Tests: 1. Observations are independent of each other 2. Observations are random p. 32
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Inferential Statistics Parametric Statistic Assumptions 1. The sample is normally distributed. 2.
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This note was uploaded on 01/23/2012 for the course BIOL/EVPP 307 taught by Professor Crerar during the Summer '11 term at George Mason.

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Ecological Data Analysis - Ecological Data Analysis Mrs....

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