A completely randomized (CRD) experiment was conducted in a glasshouse to test whether mature sugar beet roots are heavier when using a new fertilizer (A). Twenty pots of equal size were filled with the same compost and randomly placed on the bench in two parallel rows as shown below. To ten of pots the old fertilizer (B) was added, and to the other ten pots the new fertilizer (A) was added. Sugar beet seedlings of the same age and similar size were then planted into these pots.
(i) Use descriptive statistics and graphic display to present the results. Are the parametric assumptions met? With reference to the test assumptions, choose a statistical test to determine whether the new fertilizer produces heavier sugar beet roots than the old fertilizer.
(ii) State the null hypothesis and analyze the data. Interpret the results using 95% confidence limits and the test of significance. Is there evidence that the average weight of roots is increased by using the new fertilizer?
(iii) Suggest an improvement in the design of this experiment? Are there any disadvantages to the new design?© BrainMass Inc. brainmass.com October 24, 2018, 9:26 pm ad1c9bdddf
Bench side next to the window, facing south
Old (B) Old (B) Old (B) New (A) New (A) Old (B) Old (B) New (A) Old (B) Old (B)
New (A) Old (B) New (A) New (A) Old (B) New (A) New (A) Old (B) New (A) New (A)
Unfortunately, two of the pots were damaged during the experiment and had to be discarded. The following weights (g) at maturity were recorded.
Mass of mature sugar bee roots in grams (g)
Old fertilizer (B) 48.2 54.6 58.3 47.8 51.4 52 55.2 49.1 49.9 52.6
New fertilizer (A) 52.3 57.4 55.6 53.2 61.3 58 59.8 54.8
(i) Use descriptive statistics and graphic display to present the results. Are the parametric assumptions met? With reference to the test assumptions, choose a statistical test to determine whether the new fertilizer produces heavier sugar bee roots than the old fertilizer.
I did all of this in SPSS, but you can use Excel or any other statistical program to get the same results.
First, the descriptive statistics:
The plants with the new fertilizer have a ...
Statistics Questions - quasi-experiments
A. Complete Jackson Even-numbered chapter exercises, p, 360
1Describe the advantages and disadvantages of quasi-experiments? What is the fundamental weakness of a quasi-experimental design? Why is it a weakness? Does its weakness always matter?
2If you randomly assign participants to groups, can you assume the groups are equivalent at the beginning of the study? At the end? Why or why not? If you cannot assume equivalence at either end, what can you do? Please explain.
3Explain and give examples of how the particular outcomes of a study can suggest if a particular threat is likely to have been present.
4Describe each of the following types of designs, explain its logic, and why the design does or does not address the selection threats discussed in Chapter 7 of Trochim and Donnelly (2006):
Non-equivalent control group pretest only
Non-equivalent control group pretest/posttest
5Why are quasi-experimental designs used more often than experimental designs?
6One conclusion you might reach (hint) after completing the readings for this assignment is that there are no bad designs, only bad design choices (and implementations). State a research question for which a single-group post-test only design can yield relatively unambiguous findings.
Part II - Answer the following questions:
1What research question(s) does the study address?
2What is Goldberg's rationale for the study? Was the study designed to contribute to theory? Do the results of the study contribute to theory? For both questions: If so, how? If not, why not?
3What constructs does the study address? How are they operationalized?
4What are the independent and dependent variables in the study?
5Name the type of design the researchers used.
6What internal and external validity threats did the researchers address in their design? How did they address them? Are there threats they did not address? If so how does the failure to address the threats affect the researchers' interpretations of their findings? Are Goldberg's conclusions convincing? Why or why not?
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