Student’s f-test

Student s f-test. This is a test1 used for small samples its purpose is to compare the mean from a sample with some standard value and to express some level of confidence in the significance of the comparison. It is also used to test the difference between the means of two sets of data x, and x2. 

Assessments of risks associated with the use of chlorpyrifos insecticide products for workers have been made. The assessments are based on the results of field studies conducted in citrus groves, a Christmas tree farm, cauliflower and tomato fields, and greenhouses that utilized both passive dosimetry and biomonitoring techniques to determine exposure. The biomonitoring results likely provide the best estimate of absorbed dose of chlorpyrifos, and these have been compared to the acute and chronic no observed effect levels (NOELs) for chlorpyrifos. Standard margin-of-exposure (MOE) calculations using the geometric mean of the data are performed however, probability (Student s f-test) and distributional (Monte Carlo simulation) analyses are deemed to provide more realistic evaluations of exposure and risk to the exposed population. 

The results from using the Student s f-test for a distributional analysis are presented in Table 4. These results indicate the probability of a given worker in the listed scenario exceeding the NOEL of the toxicity endpoint. The probability of exceeding the LOEL and of thus experiencing a depression of plasma cholinesterase activity is not given (except for chronic exposure scenarios in the "100 ug/kg bw/day" column). Hence, even these probabilities may be considered to be conservative and not fully representative of the probability of a worker actually experiencing a toxic effect. 

Influence on sensitivity can be tested by Student s f-test. The null hypothesis is H0 Sff = S ] 1 where SA]al is the sensitivity under ideal, i.e. robust conditions and Sr]f the sensitivity under the influence of i interferents and j factors ... 

The quantity of RNA extracted from FFPE cell/tissue sections by the heating and nonheating methods, and extracted from fresh cell/tissue embedded in OCT without fixation, was comparable, showing no significant difference for all yields of RNA by Student s f-test, with the exception of one sample, MDA cells fixed in formalin for 24 h (p < 0.05). 

Concentrations significantly reduced (Student s f-test, P<0.05) compared with snails on L diet. 

Using a spreadsheet function or analysis tool, perform a Smdent s f-test to compare the mean values of each of the first four wear rates with that of gold (the last value in the column) at an agreed-upon confidence level—for example, 95% confidence level. If you have not yet learned how to do Student s f-test, check out any book on elementary statistics, and learn how to do a f-test, or use the Help menus in your spreadsheet package. The goal is to determine if the mean wear rates of the four ceramic materials are statistically different from the wear rate for gold. If done correctly, you will have performed four separate f-tests in this step. 

Attendance at scientific meetings (exemplified by attendance at the International Society for the Study of Inborn Errors of Metabolism Symposium) showed a correlation with performance (p = 0.08, Student s f-test) this reflects scientific awareness and the commitment to training shown by the participating laboratory [1]. 

Greasham and Herber (17) described in detail the statistical analyses used to identify the significance of the variables. The significance of variables was determined by student s f-test. Variables with p values <0.2 were considered significant. 

Student s f-test is performed to determine the significance of changes in clinical pathology values obtained in CD2F1 mice treated with md-LErafAON and control groups. Analysis includes both short-term and long-term treatment groups of these mice. 

Viable counts between two groups significant p < 0.01 in 18 h samples (Student s f-test). 

These were calculated statistically by determining the Student s f-test based on the values of standard deviation and standard error, which showed the... 

When two samples are veiy similar, t approaches zero when they are different, t approaches infinity. The value of f is used to calculate the P value using Student s f-test tables, given in the appendix of this book. The P value is tte probability that the two distribution means are the same that is, Aj = Ag. When the P value is greater than a critical accepted value (typically 5% [21] or the experimental error due to both sampling and size determination if it is lai ger) then the null hypothesis (Ho Aj = A2) is accepted (i.e., the two populations are considered to be the same). Ceramic powder size distributions are often represented by log-normal distributions and not by normal distributions. For this reason the t statistic must be augmented for use with lognormal distributions. Equation (2.59) can be modified for this purpose to... 

If you can assume that your data are normally distributed, the main test for comparing two means from independent samples is Student s f-test (see Boxes 41.1 and 41.2, and Table 41.2). This assumes that the variances of the data sets are homogeneous. Tests based on the t-distribution are also available for comparing paired data or for comparing a sample mean with a chosen value. 

The f-test was devised by a statistician who used the pen-name Student, so you may see it referred to as Student s f-test. It is used when you wish to decide whether two samples come from the same population or from different ones (Fig. 41.1). The samples might have been obtained from two different sources or by applying two different treatments to an originally homogeneous population. 

Fig. 2.7 Concentrations of gentamicin in plasma of horses (n = 6) after intramuscular or subcutaneous administration of gentamicin sulphate (4mg/kg). The mean values (+ SD) for AUC (subcutaneous 53.16 + 6.52 ig-h/mL intramuscular 60.79 + 11.49 pg-h/mL) were not significantly different (Student s f-test, paired comparison, P>0.05). (Reproduced with permission from Gilman et at. (1987).)...

Fig. 3.1. Significant enhancement of the nerve-stimulation-induced release of [3H]-norepinephrine, [3H]-dopamine, and [3H]-serotonin, respectively, from the isolated brain stem of the rat in the presence of p-phenylethylamine (PEA) (n = 8). Each graph bar represents the amount of the labeled transmitter in picomoles released in a 3-min collection period. See Knoll et al. (1996c) for methodology. Vertical lines above the graph bars show the SEM (standard error of the mean). Paired Student s f-test was used for statistical analysis. P < 0.05, P < 0.02, P < 0.01, P < 0.001...

Fig. 3.4. Significant enhancement of dopamine release from the substantia nigra, tuberculum olfactorium, and striatum of rats, respectively, isolated 30 min after the subcutaneous administration of a single dose of (-)-deprenyl. The amount of dopamine released from the tissue within 20 min following the administration of different doses of (-)-deprenyl was measured according to Knoll and Miklya (1995). Horizontal lines to the right of the graph bars show the SEM. Paired Student s f-test. P < 0.05, P < 0.02, P < 0.01...

Fig. 3.12. A Protective effect of (-)-BPAP in the high micromolar concentration range, with a peak effect at 10 6M concentration, against serum-free condition induced cell death in low-cell-density culture of the cerebral cortex from E17 rats. B Lack of a protective effect of (-)-BPAP under the same conditions in the low nanomolar concentration range. Experiments were carried out in triplicate. Data are the mean SEM from six independent experiments. The data were analyzed using Student s f-test after multiple comparisons of ANOVA. P value was < 0.05 compared with the results in the vehicle-treated culture. See Hamabe et al. (2000) for methodology...

Once Rm and M( m) are calculated, a significance test (i.e.. Student s f-test) is used to test the assumption that recovery is not significantly different from 1. The t value is calculated as follows ... 

The Student s f-test was used in this evaluation to determine the level of treatment observation significance, compared with the baseline measurement. Because multiple 95% Mests were used in this evaluation, the r-test table values were adjusted for the multiple estimates by means of modified a values, a, as described by Dixon and Massey [9] a = 1 — (1 — a), where k is the number of confidence levels performed in the study. 

The vast majority of quantitative research designs utilize statistics [2]. Hence, it is critical to select appropriate statistical models (e.g., linear regression, analysis of variance, analysis of covariance, Student s f-test, or others) that complement the experimental design [9-14]. Let us now briefly address the types of statistical models available, both parametric and nonparametric. 

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