DateGroup Project TaskDetails Feb 8, 9Article Analysis Due at start of class. See pgs Feb 15, 16In-class work day Discuss scientific writing, statistics, proposals Feb 22, 23Proposal Due at start of class Intro & methods for topic See pgs Mar 1, 2Start data collection Receive TA approval MarchCollect data, analyze data, write draft of paper See pgs for details on paper Mar 29, 30In-class work day Peer edit papers Apr 5, 6Final paper Due at start of class Apr 12, 13In-class work day Discuss presentations Apr 26, 27In-class presentations Present work to class See pgs Today we will Perform & understand basic descriptive statistics Understand ideas of inferential statistics (hypothesis testing) Become familiar with three statistical tests: T-test, Chi-square, Regression Select & perform appropriate statistical test for your groups question Communicate your findings in writing and in an oral presentation to your peers What do they have in common? Descriptive Statistics What are the characteristics of my data set? What does my sample suggest about the population? Center of data mean, median, mode Spread of data Variance, standard deviation, standard erro r Later well discuss, Inferential Statistics - Using data to test hypotheses Center of Data central tendency Spread of Data small variance large variance Spread of Data standard deviation From Wikipedia Spread of Data standard deviation From Wikipedia Standard Deviation vs. Standard Error Both estimate spread of data around mean Standard Deviation - Estimates variability of population around the mean Standard Error - Measures precision of sample mean standard error = standard deviation sample size Data Analysis For your groups variables, calculate: 1) Sum 5) Standard Deviation 2) Mean 6) Standard Error 3) Median 7) Variance 4) Mode (use Data Analysis ToolPak) A)Record these measures on handout B) Write 1-2 sentences on - What do these measures tell you about your data? C) Plot data in excel, sketch on pg 88 For guidance, see p (stats); (excel) (demo use of Data Analysis ToolPak) Types of Data Count Number of events (only whole #s, no fractions) Ex: # galls with evidence of predation Continuous Includes fractions/decimals Ex: Length of gallfly larvae Categorical Data fall into groups Ex: Parasitoid/Predator/None (other exs: Male/Female, Juvenile/Adult, Red/Blue) In ecology (as in science, in general), you need to use your data to test hypotheses. To test your hypotheses & to interpret your data you use inferential statistics Three types of Tests Students t-test Determine if means of two populations are considered different For continuous data SuccessFailure Treatment Treatment Chi-Square Determine if means of two populations are considered different For count or frequency data Correlation/Regression Indicates how closely two things are related to each other Question: What affects rates of play in meerkats 1)Available energy 2)Size of individual 3)Sex of pups Types of Data Count, Continuous or Categorical? Categorical Continuous Question 1: Does rate of play differ for provisioned & unprovisioned pups? Rate of play Provisioned vs. unprovisioned pups Results Unprovisioned Provisioned (Control)(Treatment) Mean = 7.3Mean = 13.5 So these are different, Right? Maybe, lets look at the spread of the data Consider Means & Variance Declaring two populations different depends on both: Means Variation For the same means, more variation = less likely means can be declared as different Use the t-test! How do you calculate the t statistic? Is the difference statistically significant? Calculate t-value from your datat calc Compare to critical t-valuet critical T-value needed for significant differences If t calc > t critical, then your group means differ significantly When t calc > t critical, your p-value (significance value) is very small P-values 0.05 indicate significant differences What is the p-value? The probability that the findings from study are due to chance. For example, a p-value of.01 (p =.01) means there is a 1 in 100 chance the result occurred by chance. The standard accepted value is 0.05 or less. Provisioned pups play more TreatmentControl p < 0.05 * Types of Data Count, Continuous or Categorical? Continuous Question 2: Does size of individuals affect rate of play? Rate of play Size of individuals The Data Weight (kg)Rate (min/hr) Larger pups play more r = 0.8 There is a positive relationship between rates of play and body weight Correlation/Regression Correlations tell you if there is a relationship between 2 variables (but provide no information on causation) Correlation coefficient ranges between -1 and 1 Regression implies that one variable predicts the other Correlation/Regression Types of Data Count, Continuous or Categorical? Categorical Count Question 3: Does sex of individuals affect the number of play events? # of play events Sex of individuals 3) Sex of the pup Study Description: Observe the frequency of play of male and female pups If sex does not determine play we would expect the probability to be 50% Data SexObservedExpected Male1115 Female1915 Data Sex(Observed - Expected) 2 / Expected Degrees of Freedom Male(11-15) 2 /15= Female(19-15) 2 /15= 1.07 Total2.14 Table pg. 189 For 1 df the critical value is < 3.84 so neither sex plays more than expected by chance Data Analysis & Conclusions 1) Write your hypotheses (null & alternative) i.e., null: no difference A = B, alternative: A > B 2) Determine which test is best for testing your hypothesis t-test, Chi-square, correlation/regression 3) Perform test in Excel (see pgs ) 4) Record degrees of freedom (df) and appropriate stat output ( T-value, Chi-square value, P-value, R 2 ) 5) On pg 89, write -Statistical conclusion Significant difference or not? How do you know? -Biological conclusion What does the statistical conclusion mean for your hypothesis? Explain. -Reference graph in conclusion 6) Prepare a few PPT slides (