For this problem I have already done the summary for central tendency but am having trouble deciding which analysis to run now in r. Should I run a t test and anova or am I looking to do correlation and linear regression.
1. Summarize the data (measures of central tendency and variation when appropriate) both in computing simple summary statistics and in writing, briefly (1-3 sentences) discuss the nature of the data. 2. What statistical analysis and WHY a. Clearly state the statistical hypotheses. b. Any data transformation required to conduct the analysis? Or outliers? i. Think about what are the data assumptions for that test, does the data match those assumptions? C. Any post-hoc analyses that may be required. This includes model fit where appropriate. 3. Interpretation of the statistical analyses should be summarized in writing. This includes: a. Accept/reject null or alternative hypotheses b. Where, if applicable, report any differences that occur or any equations (e.g. regression). Statistical tests simply tell us that there is or there is not a difference. Back up your finding of the statistical test by reporting the appropriate information regarding the data that may give insight into the magnitude of the differences that you found. 4. Answer by writing in complete sentences, as a biologist and based on your statistical analyses, the main research question asked within each question.
1. (30 points) Certain flowering trees may flower earlier in the spring in response to fertilizer type. The campus arborist decided to run an experiment to test the effects of nitrogen (N) and phosphorus (P) fertilizer on the timing of flowering ('Flowering' in days) on trees. Specifically, the arborist wanted to see if N, P, or NP ('fertilizer') additions altered the timing of 'Flowering' (weeks since March 1) of 2 different tree species 'species', Magnolia vs Wisteria). Use the data set 'Flower.xlsx' to answer the question, Was there an effect of fertilizer and tree species on the timing of flowering? I
A 0 D Fertilizer Flowering N N N N 2.2 P 2.4 P 1 Species 2 Magnolia 3 Magnolia 4 Magnolia 5 Magnolia 6 Magnolia 7 Magnolia 8 Magnolia 9 Magnolia 10 Magnolia 11 Magnolia 12 Magnolia 13 Magnolia 14 Wisteria 2.7 NP NP 3 NP NP N 15 Wisteria N 16 Wisteria N 1 17 Wisteria N 0.9 18 Wisteria 19 Wisteria P 2.8 20 Wisteria P 21 Wisteria P 22. Wisteria NP 0.7 20 Wisteria NP 24 Wisteria NP 0.6 25 Wisteria NP
1. Summarize the data (measures of central tendency and variation when appropriate) both in computing simple summary sta
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1. Summarize the data (measures of central tendency and variation when appropriate) both in computing simple summary sta
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