Free sample   Statistics assignment on topic effects of recycled dairy effluent on pasture growth and soil composition

## Statistics assignment on the topic effects of recycled dairy effluent on pasture growth and soil composition

Question

Task: Write a statistics assignment on the effects of recycled dairy effluent on pasture growth and soil composition. Use statistical data within Australian agriculture mainly Victoria and NSW to establish your points.

Four section of the statistics assignment
1. Study Design

As per provided details, the statistics assignmentstudy is based on “effect of recycled dairy effluent on posture growth and soil composition. However, the manure is significant for this case, the production data has been obtained from the various dairy cattle, considering cows in milk and dry for specific years of span Valencia Gica.et.al.(2012). For this statistics assignment, the statistical data selected for 2015-16 years, an Australian statistical Geography standard, which is integral segment of the ABS geographical framework, whereas the data has been considered a collection and dissemination of the geographical classification statistics. For this statistics assignment, the statistical area 2 are the fundamental purpose with medium sized area, demonstrate the community which co-operates as considering social, economic and conventional have the population series of 3000 to 30,000 persons.

2. Statistical analysis in the statistics assignment;
The descriptive statistics are the conventional statistics method which provides the brief informational co-efficient which can summarized the given data sets that can be either the demonstration of the complete population or the specific sample population. This method mentioned in the statistics assignmentcan separate in order to measure the central tendency and measures the variability as well.

However, this method uses for mainly two purpose i.e. providing basic details and information about variables in the dataset, and demonstrate the conventional or potential relationship between the variablesGray.et.al.(2021). For this statistics assignment, there are mainly three conventional and common descriptive statistics can be highlight graphically or pictorially and evaluate through graphical or pictorial method as well.

3. Presentation of results of the statistics assignment
Dairy_cattle - Cows in milk and dry (no.)

 Dairy_cattle - Cows in milk and dry (no.) Mean 3127.421053 Standard Error 919.7844533 Median 1102 Mode #N/A Standard Deviation 4009.247482 Sample Variance 16074065.37 Kurtosis 0.023311161 Skewness 1.289898334 Range 11462 Minimum 45 Maximum 11507 Sum 59421 Count 19 Percentiles P10 10% 72 P25 25% 604.5 P50 50% 1102 P75 75% 2825.75 P90 90% 9453.6 P99 99% 10561.71

For “Total residues”:

 TOTAL_RESIDUES Mean 6513.684211 Standard Error 1914.718548 Median 2288 Mode 156 Standard Deviation 8346.064655 Sample Variance 69656795.23 Kurtosis 0.026575315 Skewness 1.290614068 Range 23868 Minimum 104 Maximum 23972 Sum 123760 Count 19

For “total dry residues”:

 Total_dry_residues (t/yr) Mean 631.3157895 Standard Error 185.5632181 Median 222 Mode 15 Standard Deviation 808.8513153 Sample Variance 654240.4503 Kurtosis 0.025847201 Skewness 1.290281071 Range 2313 Minimum 10 Maximum 2323 Sum 11995 Count 19

 Number_of _businesses Mean 9.684211 Standard Error 2.5593 Median 5 Mode 1 Standard Deviation 11.15573 Sample Variance 124.4503 Kurtosis 2.693913 Skewness 1.823871 Range 40 Minimum 1 Maximum 41 Sum 184 Count 19

4. Interpretation of results
As shown in above obtained results mentioned in thestatistics assignment, the data demonstrate the dairy cattle cows in milk and dry feature, total residuals, total dry residuals and numbers of business associate with the dairy segment.

Discussion
The statistical data of the statistics assignmentsuggest and demonstrate the individual parameters such as mean, standard deviation, maximum and minimum.
In first case of thestatistics assignment, the standard deviation found as 4009.2474, whereas mean value observes as 3127.421, maximum value obtained as 11507 and minimum value find as 45. The standard deviation suggest that the data varies in specific range. In general, the standard deviation suggest that how detached the data set is. The magnitude indicate the specific rangeChisholm.et.al.(2021). That compares each data point to the mean of all data points, and standard deviation returns the calculated outcome which describes as the data point are in the close proximity or whether it is spread around. The date set varies in large range. Secondly, the mean value indicate the data set has been varies in the range of “3127.42”.

Identification the choice made in each of the four areas
From the above four provided different area, it is recommendin the statistics assignmentto select the area based on the “numbers of business” based on selection. For this case, the standard deviation, mean, mode, median and provided value has been acceptable and desirable level.

Review of those choice in the statistics assignment
The selection of the choice based on business priory, however, this is most suitable and desirable range of “standard error” consideration. For this statistics assignment, the standard error has been achieved as 2.55 which is considerable low and conventionally neglected in term of precise outcome. Based on provided location, the selected choice has significant and acceptable for the procedure as well.

References
Chisholm, C.M., Cameron, K.C., Di, H.J. and Green, T.C., 2021. The effect of polyferric sulphate treated farm dairy effluent and clarified water on leaching losses, greenhouse gas emissions and pasture growth. New Zealand Journal of Agricultural Research, 64(3), pp.271-285.
Gray, C.W., Lucci, G.M. and Cavanagh, J.A., 2021. Can the application of farm dairy effluent enhance cadmium leaching from soil. Environmental Science and Pollution Research, 28(36), pp.50919-50929. Valencia Gica, R.B., Yost, R.S. and Porter, G., 2012. Biomass production and nutrient removal by tropical grasses subsurface drip irrigated with dairy effluent. Grass and forage Science, 67(3), pp.337-349.
https://www.agriculture.gov.au/search search_api_fulltext=dairy%20effluent&f%5B0%5D=taxonomy_content_type_media%3A839&page=0
https://catalogue.data.wa.gov.au/dataset/dairy-effluent/resource/c1af3f11-d386-4de7-a09c-81cf19acdc5a https://www.abs.gov.au/AUSSTATS/abs@.nsf/DetailsPage/7121.02010-11 OpenDocument https://search.abs.gov.au/s/

https://www.dairyaustralia.com.au/dairynsw/land-water-and-climate/climate/preserve#.Y0gq93ZBzIU

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