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2013 - 20196
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Subject: Agricultural Statistics and Informatics × End date: 2019 × Start date: 2010 × Type: Thesis ×
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Now showing 1 - 6 of 6
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    ThesisItemOpen Access
    A statistical study of anthropometric data of children
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-08) Pathak, Shreya; Shukla, A.K.
    Present work deals withstatistical assessment of anthropometricand body parameters of children randomly selected fromthree different states of India namely Uttarakhand, Arunachal Pradesh and Gujarat. The secondary data on Age, Body Mass Index (BMI), Height (Ht), Weight (Wt) and Mid Upper Arm Circumference (MUAC) was obtained from College of Home Science, G.B. Pant University of Agriculture andTechnology, Pantnagar. From each state data of 500 children (250 boys and 250 girls) wererandomly selected.Following major conclusions were made on the basis of present study: 􀁸 The distributionpatterns of anthropometric parameters were carried out with the help of EasyFit5.6 Professional software and testing of their goodness of fit by Kolmogorov Smirnov and Chi-square tests. It was concluded that the distribution patterns of anthropometric parameters Height, Weight and MUAC were dissimilar and behave differently for different age groups in children.As none of the anthropometric parameters viz. Ht,Wt and MUAC follow normal distribution it was also concluded that the non -parametric test will provide more precise conclusions as compared to parametric test for statistical analysis of these parameters. 􀁸 Spearman’s Rank Correlation Coefficient was used to study inter relationship between anthropometric and body parameters of children from three different states and the significance of these coefficient was tested by t-test.It was concluded that all the parameters viz.Age, Ht, Wt, BMI and MUAC are significantly positively correlated to each other. 􀁸 Linear Regression (LR) and Multiple Linear Regression (MLR) analysis were used to develop prediction models for BMI and MUAC in children using IBM SPSS Statstics20 software. Out of the 14 LR and 7 MLR prediction models developed for BMI, it was concluded that the best fitted LR model to estimate BMI is LR4(r2=0.980) taking Age as the only predictor and the best fitted MLR model to estimate BMI is MLR1 (R2=0.988) taking MUAC and Age as the predictors.Similarly, out of the22 LR and14MLR prediction models developed for MUAC, it was concluded that the best fitted LR model to estimate MUAC is LR12 (r2=0.887) taking Htas the only predictor. Similarly, the best fitted MLR model to estimate MUAC is MLR9 (R2=0.89) taking Ht, Wt and Age as the predictors. 􀁸 Kruskal Wallis, One way ANOVA and Z test were used for age –wise, state- wise and gender - wise comparison of different parameters. It was concluded there is a significant difference with respect to all the parameters Ht, Wt, BMI and MUAC in different age groups of children within the state and between the states. Similarly, gender-wise significant difference was obtained with respect to all the parameters in each state. The findings of the study are expected to provide useful information for health experts and policy makers to initiate healthy intervention programmes at school level.
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    ThesisItemOpen Access
    Assessment of trends and variability of precipitation and temperature for Chandigarh
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-06) Singh, Tejendra; Ahmad, Haseen
    The present investigation was carried out to study the weather parameters viz. precipitation, maximum temperature, and minimum temperature for Chandigarh over the period of 102 years (1901-2002). The data were collected from Indian Water Portal website www.indianwaterportal.org. The objectives of the study were to analyze the trends, variability and distribution fitting for weather parameters on annual, seasonal and monthly basis. Different measures of statistics viz. mean, standard deviation, skewness, kurtosis, etc. were calculated to test the normality of weather parameters by using Microsoft Excel and IBM SPSS 16.0. The values of γ1≠0, β2≠3, shows that the weather parameters did not follow normal distribution. A comparative study was made among the weather parameters by fitting a trend line by using the method of least squares to obtained best-fitted trend line. The study of best fit distribution was carried out by using EasyFit 5.5 software. The study showed significant increasing trends for winter and monsoon seasons precipitation whereas annual, monthly, premonsoon season and post-monsoon season precipitation showed insignificant increasing and decreasing trends. For maximum and minimum temperatures, winter and pre-monsoon seasons showed significant increasing trends while monsoon and post-monsoon seasons showed significant decreasing trends. Annual minimum temperature showed significant increasing trend whereas annual maximum temperature showed insignificant increasing trend. Monthly minimum and maximum temperatures showed insignificant increasing trends.
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    ThesisItemOpen Access
    Effects of tillage operations and weed control measures on soil variables and soybean yield
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2019-06) Wamanrao, Agashe Nehatai; Vinod Kumar
    The object of this study was to use an appropriate statistical method for analyzing the experimental data. The data were collected from the research farm of A.I.C.R.P. on Weed Management, Department of Agronomy, Dr. P.D.K.V., Akola (Maharashtra) during the year 2016-17. The effect of tillage practices on the soil characteristics and growth components were analyzed by two different methods viz., repeated measures in strip plot design and multi-observation data (measurement over time) in strip plot design. The power of the test for both the methods was nearly equal. Consequently any one of these two methods may be used for the analysis. The soybean yield data were analyzed by two methods viz., ANOVA and ANCOVA. Analysis of covariance with two covariates i.e. number of grains per plant and number of pods per plant was preferred for improving the precision of the experiment. The results obtained from correlation and path coefficient analysis strongly indicate that number of branches per plant, number of pods per plant and number of grains per plant should be considered as indices for selecting high yielding soybean variety.
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    ThesisItemOpen Access
    Study of climatic parameters and climate change in capital of Himachal Pradesh and nearby districts
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-06) Chauhan, Sapna; Ahmad, Haseen
    Climatic variability, particularly, that of the precipitation, minimum temperature and maximum temperature has received a great deal of attention worldwide. The present study is carried out to determine the climatic conditions that are annually, monthly and seasonally variable to weather parameters in the Capital of Himachal Pradesh (Shimla) and nearby districts based on the data collected from Indian water portal website www.indianwaterportal.org. Three weather parameters were studied viz. precipitation, minimum temperature and maximum temperature. For the study of the three climatic parameters which showed linear trend annually, monthly and seasonally and different measures of statistics viz. mean, median, variance, skewness, standard error, range, minimum, maximum values and confidence interval for median etc. were calculated by Microsoft Excel and IBM SPSS software. A comparative study was made among the three climatic parameters for 102 years (1901-2002) by fitting a trend line by method of least squares to obtained best fitted straight line trend. The normality of climatic parameters were also studied by calculating the skewness and kurtosis which showed that the climatic parameters were skewed that is _1_ 0, _2_3 which showed a nonnormal distribution. Then studied the best fit distributions by using Easy Fit software. The graphs of precipitation showed a decreasing trends while minimum and maximum temperature showed an increasing and decreasing trend annually, monthly and seasonally in Capital of Himachal Pradesh (Shimla) and nearby districts.
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    ThesisItemOpen Access
    Statistical analysis of soil characteristics data
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2018-06) Mishra, Baishali; Vinod Kumar
    The object of this study was to analyze the soil characteristics (pH, EC, OC, Nitrogen, Phosphorus, Potassium, Sulphur, Maganese, Iron, Zinc, Copper and Boron) data through Distribution fitting, ANOVA, Multiple Correlation and Regression analysis and Path coefficient analysis. Secondary data on the above said soil characteristics of Mirzapurdistrict were analyzed with the help of different softwares. Different soil characteristics are found to follow different best fitted distributions. Average soil characteristic contents are found to be significantly different in all tehsils and also at different elevation ranges. pHhas shown significant positive correlation with Sulphur and Boron and significant negative correlation with Nitrogen, Maganese and Iron. EC has shown significant and positive correlation with Potassium, Sulphur and Boron and significant negative correlation with Iron, Maganese and Zinc. Moreover, OC is found to have positive and significant correlation with all the nutrients except Nitrogen. Path coefficient analysis reveals that EC, OC, Sulphur, Copper and Boron have positive direct effects on soil pH and remaining have negative direct effects on soil pH. Multiple Linear Regression Models are developed for estimating soil properties (pH, EC, OC) on the basis of given values of soil nutrients. These models are found to be quite efficient for the said purpose on the basis of large value of R2and small value of Root Mean Square Error.
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    ThesisItemOpen Access
    Systematic sampling for milk yield data
    (G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2013-07) Pandey, Tanuj Kumar; Vinod Kumar
    The present study uses systematic sampling procedures for milk yield data exhibiting some non-linear trends. The data relate to milk yields of four breeds of cows (two brands S16 and S19 of Sahiwal cows and two brands X124 and X205 of crossbred cows) and one breed (Murrah brand no. M125) of buffaloes over one lactation period during 2011-2013. The best fitted mathematical forms of non-linear trend present in the milk yield data are obtained and the expressions of average variances of the estimators of population mean under simple random, usual systematic and modified systematic sampling procedures by taking into account the trend present in the data have been derived from the formulae already derived by Ashutosh (1995) for populations showing general trend. A comparative study is made among these three sampling procedures for five data sets by calculating average variances using best fitted trend equations. Usual systematic sampling is found more precise than simple random and modified systematic sampling procedures for four data sets whereas modified systematic sampling is found better than the other two procedures for one data set. Stratification of milk yield data has resulted in the significant reduction of average variances under all the three sampling schemes. The distribution of milk yield is found to vary from one data set to another. Dagum (4P) distribution is found the best fitted distribution for milk yield of Sahiwal cows, whereas for crossbred cows with brand numbers X124 and X205, it is Gumble Min. and Lognormal respectively. Moreover, the distribution of milk yield of Murrah buffaloes brand number M125 is general extreme values.