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# Class Note for Stat 412 at WSU

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COURSE
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TYPE
Class Notes
PAGES
44
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KARMA
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This 44 page Class Notes was uploaded by an elite notetaker on Friday February 6, 2015. The Class Notes belongs to a course at Washington State University taught by a professor in Fall. Since its upload, it has received 16 views.

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Date Created: 02/06/15
Brian T1i39eszasot Washington University Vancouver Lecture overview 1 Objectives amp Challenges 2 Design 3 Execution 4 Management Experimental Design Scientific study of the natural world Maior components 1 Scientific method 2 Experimental design 3 Statistical analysis Objectives How can I design a study that Will be able to detect meaningful biological Changes with a reasonable amount of effort Major Challenges 1 Poor understanding of question 2 Poor design Lack of proper replication Lack of statistical power to detect changes Major Components 1 Design 2 Execution 3 Management Define the Problem Be able to concisely state to someone else the guestion you are asking Your results will only be as coherent and comprehensible as your initial conception of the problem Define the Population Clearly define the statistical population to sample Define the statistical population precisely on a local scale Statistical Population The study area of interest Limits the scope of inference ls large relative to our ability to obtain information Census vs Sample Transect amp Quad rats Census vs Sample Census vs Sample Census vs Sample Sam Ie Census vs Sample Statistical analysis Populations are large we are small Our inferences are limited and imperfect Need to use rigorous design Answer questions with degree of uncertainty eg probabilities Replication Take independent replicate samples within each combination of time location and any other controlled variable Lack of independence Pseudoreplication Replication Repeated independent sampling of environmental responses eg Quadrats along a transect Replication Replication must occur in each sampling subunit Site 1 Site 2 Shallow Shallow mm Deep Deep QUEST Sampling Design m Power amp Sample Size Calculate appropriate sample size based on power analysis Power ability of statistical test to reject a false null hypothesis 03H1lvl2 13H1 H2 Statistical Errors Reality HO True H0 False Io T II E 39 e rror 8 OK yp 8 B Results lt of test IO 6 a Type I error 3 OK C or Consequences of errors Typel Typell Experiment Monitoring False Effects False Alarm Undetected Undetected results impacts Factors Influencing Power 1 Algha as GT TB SHOW3 2 V ri n 2 Minimize by a a ce aso T TB design 3 Sample size as nT TB 52 Power Curves TTest T W Minimum n n z X12 Power Curves Power Analysis Power Analysis Average coral cover Average sh abundance Kapoho Hawai39i Molokini Maui 300 300 D D u u m 200 n 200 D D E E E E N N I I E E 5 5 E 100 a E 100 a E E E E o o t o 10 20 30 4o 50 o 10 20 30 4o 50 Minimum detectable difference Minimum detectable difference difference between means difference between means Minimum sample size 300 Power Analysis Total coral cover 200 100 Kapoho I Puak o Molokini OI 005 3 010 Optimal sample size given accurate vs effort I I I I 10 20 30 4O 50 Minimum detectable difference difference between means Control vs Impact To test whether a condition has an effect collect samples both where the condition is present and where the condition is absent but where all else is the same An effect can only be demonstrated by comparison to a control Coral reef u n Control Before vs After To test whether a condition has an effect collect samples both before the condition is present and ier the condition is absent but where all else is the same An effect can only be rigorously demonstrated by before vs after comparisons Coral reef BACI BeforeAfter ControlImpact Comparison Procedure Before After Control A Density Time P CIFlE ERIEfo Mazzaella flaccida Iridescent seaweed Mean Cover 75 50 25 0 Contro n 1978 1981 1984 1987 Time 1991 1995 Mean Cover Mean Cover 75 50 25 75 50 25 Control 1978 1981 1984 1987 1991 1995 Time Impact 1978 1981 1984 1987 1991 1995 Time 75 Mean Cover 0 75 Mean Cover 50 25 50 25 Control 1978 1981 1984 1987 1991 1995 Time 1978 1981 1984 1987 1991 1995 Time BACI T I T There is a greater difference WO39Samp e 39teSt39 between control and impact sites Before VS After after the Plant began than before However there is lt1 DF 6 T 53955 P lt 03901 possibility that this difference is due to chance O l O Difference In Mean Cover N 01 Difference 0 1978 1981 1984 1987 1991 1995 Ti me Mill Creek On WSU Vancouver campus New culvert installed in summer 1999 SEPA Mitigated DNS Erosion minimized through sit fencing Maintained during construction Disturbed slopes reseeded within 24h i w i it 455i T3 if 12 YSI Multiprobe Sonde Measured temperature 02 turbidity Before during and after construction Turbidity NTU Mill Creek WA Water quality during WSU culvert construction 1000 PreConstruction Baseline August 1999 100 Rain Event 10 1 I 8102099 8122099 8142099 8162099 Turbidity NTU Mill Creek WA Water quality during WSU culvert construction 1000 PreConstruction Baseline August 1999 Rain Event 100 10 1 I 39 8102099 8122099 8142099 8162099 1000 Construction AugSept 1999 100 ll 4 10 1 u v v v 39 I I I 8282099 8302099 912099 932099 952099 MuWWW 972099 992OE Turbidity NTU Mill Creek WA Water quality during WSU culvert construction 1000 PreConstruction Baseline August 1999 Ram Event 100 10 1 I 39 39 8102099 8122099 8142099 8162099 1000 Construction AugSept 1999 100 39 I H g 4 10 3J4w m 1 I I I I I I I I I I I I I I I I I I I I I I I I I I I I I I 8282099 8302099 912099 932099 952099 972099 99209 1000 PostConstruction SeptOct 1999 100 10 1 I I I I I I I I I I I I I I I I I I 9222099 9262099 9302099 1042099 1082099 10122 Execu on 1 Write clearly and legibly use numbers or scratch marks but not both review data sheet after dive complete and readable Standardize how the data are taken or control for their effect by design eg protocols and QC Minimize measurement error by using the same equipment compared to a standard If repeatedly sampling same site affix permanent markers to accurately locate study areas ie minimize between survey habitat variability Data Management 1 Have a data manager Assign one person to collect and hold data Always make copies after field work Design data sheets to collect data for easy entry into the computer Verify entered data against raw data Make backup copies of data files

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