Computer Software Application on Aquaculture
Your grade depends on: 1. Correctness of programming upon the requests in the questions, 2. Syntax error, 3. Structure and notes on the programming, e.g.,
sub-setting, comments, designation of variables, titles, etc., and 4. Interpretation of the printouts.
Attached your answer in two files: 1. a SAS program file, 2. a word file of the answers to the questions by its order. Submit it to my box (yhchien@https://www.doczj.com/doc/6f6041482.html,.tw) before 17:00 of June 26 (Thu.)
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I. (10%) The following data are the number of fish caught by a standardized sampling gear (an indication of fish survived) in each of the 9-week experiment period. A decaying exponential equation or survival model is used to present the survival condition over the whole experiment period. Fit the given data to the equation: Nt = No x exp (-z x t), where Nt is the number of fish survived at week t, No the number of fish at stocking, z the weekly instantaneous mortality coefficient, by using
1.Direct fitting method, and
2.Log-transform to linear method.
Provide the following answers:
(1) What are the estimates of No and z?
(2) A plot showing the observed and the predicted and a plot for residual distribution. (Data for question I is on attached file Q1data)
II. (20%) This question is to test your ability how to reorganize data sets, differentiate some parameters expressing variability, and examine relationships between two
(2) Get the summary statistics: mean, standard deviation (std), standard error (stderr), and coefficient of variation (cv) of both height (ht) and weight (wt) and show me and prove to me the mathematical relationships: a. between standard deviation and standard error, b. between cv and mean;
(3) Compare the variation between ht and wt;
(4) Plot out: (a) an overlay plot of both ht and wt versus age and (b) a plot of wt versus ht; and
(5) Fit the data into a weight-length(height) equation: wt=a*ht**b by: (a) Non-linear direct fitting and (b) log-transformed linear fitting (hint: log(wt)=log(a)+b*log(ht). (Data for question II is on attached file Q2 data)
III. (30%) Below is an experiment conducted to find out the effect of vitamin E deficiency on growth of a certain animal. CWT is the final weight of control group receiving normal diet for a month and DWT the final weight of vitamin E deficiency group. Animals were divided into 5 size classes based on their pre-treatment weight.
(1) Use pair-t test to test the difference of their final weight and interpret the SAS printout;
(2) Analyze the same data set by two-way ANOV A;
(3) Disregard their size class as the experiment would have been conducted with 10 random groups, among them 5 receive normal diet and the other 5 vitamin E deficient diet and reorganize the data set into 10 observations of 2 variables (trt: C and D, and wt) by programming. (hint: use drop statement to retain the variables you want them to stay then create a variable trt. data control; set all; drop size dwt; wt=cwt; drop cwt; trt='c'; proc print;). Use unpair-t test to test the difference of their final weight;
(4) Analyze this new data set by one-way ANOV A;
(5) Show me F=t2 in both cases, namely, 2-way ANOV A= pair-t and 1-way
ANOV A=unpair-t; and
(6) Compare the results of using two types of analysis and make your own comments. (Data for question III is on attached file Q3 data)
IV. (40%) An experiment was conducted to find out the effects of various sources and levels of carotenoids on the pigmentation of various parts of an ornamental fish, blood parrot. Seven diets (trt): C, A8, A16, B8, B16, H8, and H16 were fed to the fish for 8 weeks, where ‘C’ stood for control diet, which no carotenoid was supplemented, ‘A’ for diets supplemented with astaxanthin (pure and synthetic) from Carophyll Pink (DSM), ‘B’ for diets supplemented with β-carotene (pure and synthetic) from Rovimix β-carotene (DSM), ‘H’ for diets supplemented with algae Haematococcus pluvialis(mainly astaxanthin mixed with other carotenoids and natural), ‘8’ for diets supplemented with one carotenoid from the above 3 sources at a concentration of 80 mg/kg, and ‘16’ for 160 mg/kg. Total 21 aquaria (experimental units) were used so that each treatment had 3 replicates (rep). When the rearing completed, fish survived were dissected into 6 parts to analyze for body content of astaxanthin (in data AA) and β-carotene (in data BB). Here only the pigmentation on fin is used: af and bf. (1) Merge these two data sets by trt and rep, create two new variables: total carotenoid (cf=af+bf) and ratio of astaxanthin toβ-carotene (rab=af/bf);
(2) Conduct a one-way ANOV A on 7 treatments, followed by Duncan’s multiple range test (DMRT);
(3) Conduct an orthogonal contrast for the following 6 comparisons:
(i) Control vs. pigmented, (ii) Astaxanthin (A’s and H’s) vs.β-caroten e (B’s), (iii) Astaxanthin: Synthetic (A’s) vs. Natural (H’s), (iv) A8 vs. A16, (v) B8 vs. B16, and (vi) H8 vs. H16.
(4) Drop Control so that the remaining 6 treatments become 2 (concentrations: 80
mg/kg and 160 mg/kg) X 3 (types of carotenoid: A, B, and H). Split one independent variable trt into two independent variables (or factors): con and type (if trt=’H16’ then con=16 and type=’H’;). Now you can perform a two-way ANOV A with and without interaction, followed by DMRT, on 4 dependent variables: af, bf, cf, and rab.
(5) Interpret the results obtained.
(Data for question IV is on attached file Q4 data)