A test of Lamarckian theory over 50 generations of rats The assessment for the Thinking with data module is described here. The relevant data are in the worksheet: rats_50.xls (MacOS users: rats_50.mwx). These data arise from a remarkable experiment carried out in the Department of Zoology at the University of Melbourne, over 22 years. Wilfred Agar, Frank Drummond, Oscar Tiegs and Mary Gunson were the researchers involved. The experiment was a test of the theory of Lamarckian inheritance, which states that offspring can inherit characteristics that are acquired or learnt by their parents during the parents' lifetime. Agar and his colleagues' study was motivated by a well-known experiment by high profile Harvard psychologist William Mcdougall. Oscar Tiegs and William AgarData Background Powerpoint presentation The experimental setup Both series of experiments used Wistar rats, a stock of rat that is an outbred albino rat, developed at the Wistar Institute in 1906, and still currently one of the most popular rats for laboratory research. The rats had to learn to escape from a tank of water from one of two exits. The correct exit was dimly lit whereas the wrong exit was brightly lit. The bright exit was "wrong" because an electric shock was given at this exit. The intention was to induce a phobia of bright lights. Both Mcdougall and the Melbourne researchers bred rats for many generations, and if the Lamarckian view was correct, the light phobia should have been inherited by successive generations. The correct exit was alternated from one side to the other. The number of errors made in learning the correct exit was measured; the criterion for successful learning was making 12 successive correct choices. You can read about the experimental set up in more detail here: Agar, W.E., Drummond, F.H., Tiegs, O.W., and Gunson, M.M. (1954) Fourth (Final) report on a test of Mcdougall's Lamarckian experiment on the training of rats. Journal of Experimental Biology 31, 307-21. (Read pages 307 to 309). Mcdougall's experiments Mcdougall began experimenting in 1920 and bred many generations of rats over many years. The rats to be bred from one generation were randomly chosen. The rats studied were successive generations of trained rats. Here is a figure showing data reported by Mcdougall in 1938. 80- 50 Average number of errors 10 15 20 25 30 35 40 45 Generation Mcdougall interpreted the decline in the average number of errors as providing good evidence for Lamarckian theory. Here is the reference to Mcdougall's 1938 paper: McDougall, W. (1938) Fourth report on a Lamarckian experiment (Part 1). British Journal of Psychology. General Section. 28(4), 321-334.The Melbourne experiments The Melbourne researchers bred 50 generations of rats over 20 years from 1932. All the rats were descended from a single pair. Here is Agar et al.'s (1954) description of the study design: "The rst generation obtained from this pair (whidt was not trained) was divided into two groups, one of which was trained and became the ancestors of the trained line (T). The other group was not trained and became the ancestors of the control line (C). In each generation the required number of rats of the trained line was trained and mated as parents of the next generation. In the control line some litters were not trained but were kept as parents of the next generation, other tters of this line were trained to provide controls to the same generation of the trained line. These trained controls were, of course, not used for breeding. In this way each generation of the trained line was tested against an approximately equal number of controls, differing from the trained line only in the fact that their ancestors were not trained." (p.309) There were four articles published on the study by Agar and his colleagues, from 1935 to 1954. In the worksheet, rats_50.xls, each line represents the result of a single rat. The variables in the worksheet are: Column Label Variable C1 Date reported Year of the article reporting the result C2 Generation Generation of the rat C3 Group Trained = Rat with trained ancestors Control = Rat without trained ancestors C4 Subgroup As for group, but in later generations were divided into subgroups. C5 Number of errors The number of errors prior to the achievement of \"learning" (12 consecutive successful trials) or until special training was provided. C6 Special training [1 = no special training; I = special training Note that there were no differences in treatment of the subgroups within the Training or Control groups. The subgroups were formed to avoid potential mutations accumulating in the groups of rats. Note that the maximum number of errors is 151; this corresponds to failing to learn by the 52nd day of training, as explained by Agar et al. (1954): \"A small proportion of rats, that had failed to solve the problem by the 52nd day of training, were given 'special training'. They were, almost without exception, rats that had developed the habit of going exclusively to one ramp and were quite unable to solve the problem because of unawareness of the alternative exit. \"Special training' consisted in forcing the animals, usually against strong resistance, to take the correct pathway. Training of all rats was continued after learning was complete, and until the time of mating, but was limited to two rims per day.\" (p.303) IEull taper here] The actual number of errors was not reported by the researchers for rats who had 'special training'; in le data set, they are recorded as having made 15-1 errors, which is the average number expected over the number of trials run until the 52nd day, if the rats were guessing. Data Background Powerpoint presentation Assessment requirements The assessment requirements involve: . providing appropriate summary measures and graphs to evaluate the evidence in the Melbourne researchers' data, . reporting on the interpretation of the data in relation to the Lamarckian claims, completing an online test addressing issues arising from the two studies involved. These requirements are detailed further below. To complete these requirements, you need to read the material provided here, including pages 307 to 309 of Agar et al. (1954). Summarising and describing the data 1. a. Use Minitab to obtain suitable summary statistics of a measure of learning: for either the number of errors or special training. Summarise the data according to generation and group. See the Minitab demos for details about obtaining summary measures. 1. b. Use Minitab to graph the summarised data in a way that allows you to consider the Lamarckian theory. Reporting on the results Create a PowerPoint presentation to explain your investigation of the Melbourne researchers' results carried out above. Your presentation should cover the following: . Background to the design of the studies (2-3 slides) . Justification and definition of the summary measures you used (1-2 slides) Graphics illustrating the results (1-2 slides) . Discussion of any patterns in the graphics presented in terms of the explanatory variables involved (1-2 slides) . Interpretation of the patterns in the data in terms of Lamarckian theory (1-2 slides) Comparison of the interpretation of the Melbourne data and Mcdougall's data (1-2 slides). You are allowed a maximum of 12 slides; presentations of over 12 slides will only have the first 12 slides assessed (this includes any title slides; including references/bibliography as a 13th slide is acceptable). It will be graded according to this rubric & Since you will not actually present your report, your slides will need a little more information than would normally be expected in a presentation, but should not have excessive amounts of text. You should ensure your slides could easily be read from a distance, if you were giving an actual presentation. Submit your work here. We recommend that you save the Powerpoint as a PDF file. The submission system automatically converts the Powerpoint to a PDF, and your original formatting may be corrupted in this process. Your formatting will be preserved if you first convert the Powerpoint to PDF