Download Applied Statistical Methods in Agriculture, Health and Life by Bayo Lawal PDF
By Bayo Lawal
This textbook teaches an important statistical ways to solution study questions utilizing a different variety of statistical software program courses, together with MINITAB and R. This textbook is built for undergraduate scholars in agriculture, nursing, biology and biomedical learn. Graduate scholars also will locate it to be an invaluable option to refresh their information talents and to reference software program suggestions. the original mix of examples is approached utilizing MINITAB and R for his or her person strengths. matters lined contain between others facts description, likelihood distributions, experimental layout, regression research, randomized layout and organic assay. in contrast to different biostatistics textbooks, this article additionally contains outliers, influential observations in regression and an creation to survival research. fabric is taken from the author's large instructing and learn in Africa, united states and the united kingdom. pattern difficulties, references and digital supplementary fabric accompany every one chapter.
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Additional resources for Applied Statistical Methods in Agriculture, Health and Life Sciences
1 Weights of heads of households in kilograms 70 68 59 64 64 66 60 71 64 70 60 60 53 68 69 55 63 76 64 68 61 60 64 66 63 63 75 64 67 59 72 68 52 63 57 These data are what we call raw data, that is, data as obtained from the ﬁeld. With the data in this form, very little information can be obtained about the population. The ﬁrst possible thing that we can do is to put the data in what we call an array. An array is the arrangement of the values in ascending or descending order of magnitude. For example, if we put the data in an ascending array we have the following results: 52 60 63 66 69 53 60 64 66 70 55 60 64 67 70 57 61 64 68 71 59 63 64 68 72 59 63 64 68 75 60 63 64 68 76 B.
No. No. No. No. of of of of of of of of farmers farmers farmers farmers farmers farmers farmers farmers whose whose whose whose whose whose whose whose weights weights weights weights weights weights weights weights are are are are are are are are greater greater greater greater greater greater greater greater than than than than than than than than 52 56 60 64 68 72 76 80 kg = 35 kg = 32 kg = 29 kg = 20 kg = 11 kg = 3 kg = 1 kg = 0 The above are similarly obtained from the cumulative frequency distribution from above.
No. No. of of of of of of of of farmers farmers farmers farmers farmers farmers farmers farmers - under under under under under under under Total whose whose whose whose whose whose whose whose Frequency 56 60 64 68 72 76 80 weights weights weights weights weights weights weights weights Cumulative frequency from below Cumulative frequency from above 3 6 15 24 32 34 35 35 32 29 20 11 3 1 3 3 9 9 8 2 1 35 are are are are are are are are less less less less less less less less than than than than than than than than 52 56 60 64 68 72 76 80 kg = 0 kg = 3 kg = 6 kg = 15 kg = 24 kg = 32 kg = 4 kg = 35 The above are obtained from the cumulative frequency distribution from below.