Hypothesis Testing Sample Clauses

Hypothesis Testing. 4.6.1. Insurance productivity and the growth of Nigerian economy From the long-run coefficients displayed on Table 4, the proxy for insurance sector development and productivity (RGDPIS) was found to be a stimulant of Nigerian economic growth and it maintained positive and significant relationship with Nigerian economic growth, in a manner that increase in the insurance productivity would promote Nigerian economic growth significantly. Hence, since the probability value 0.0250<0.05, there insufficient evidence to accept the null hypothesis; hence the null hypothesis H01 which states that insurance sector productivity has no effect that is significant on the growth of Nigerian economy was accepted.
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Hypothesis Testing. The difference in the outcome of interest is calculated for each matched pair m (m= 1,2,...,M ) as ∆Ym = Ym,i − Ym,ij . The Wilcoxon signed rank test is used to test whether the difference across matched pairs is different from
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Hypothesis Testing. The use of Kappa in such a descriptive fashion for evaluating assessments does not preclude significance testing. For example, given that the expression for the standard error of Kappa under certain assumptions has been derived (Xxxxxx, Xxxxx, and Xxxxxxx, 1969), it is possible to test the null hypothesis that a value of Kappa equals zero (i.e., the value that would be obtained by chance). However, as illustrated by Henkel in the case of a chi-square test (Henkel, 1976), whether a finding is statistically significant or not (at a specific alpha level) is strongly dependent on the sample size. For example, a very low value of Kappa that is close to zero can be found statistically significant if the sample size is large enough. Conversely, a value of Kappa close to 1 may not be better than that obtained by chance if the sample size is very small. Therefore, it is also important to be able to interpret the value of Kappa irrespective of the sample size to decide if it is “clinically significant”. If the value of Kappa is greater than 0.62, and subsequent statistical testing fails to reject the null hypothesis, then there are different schools of thought that one can subscribe to depending on the consequences of an incorrect decision.11 For instance, in medicine, the drawing of conclusions from statistically insignificant results has been described as bordering on fraud (Xxxxxxx, 1990). On the other hand, in the social sciences some encourage the drawing of conclusions even from statistically insignificant results (Xxxxxx, 1955). In the context of the Kappa statistic, it has been suggested that hypothesis testing of Kappa is not needed because in practice agreement is usually better than chance anyway (Armitage and Xxxxx, 1994). Therefore, if one accepts the latter argument, then the most important issue is to interpret the actual value of Kappa rather than hypothesis testing. This argument is, however, a weak one in the context of software process assessments. Previous studies have shown that some obtained values of Kappa are not statistically significant due to extreme systematic bias by one of the assessors (Xx Xxxx, Xxxxxx, and Xxxxx, 1996). Perhaps a more parsimonious marriage of the above benchmark and hypothesis testing is to test the null hypothesis that κ ≤ 0.62. In the past a threshold of 0.4 was uncomfortably used (Xxxxxx, El Emam, and Xxxxx, 1997a). With the current benchmark, there is an initial rational basis for defining such a null hypothesis.
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Hypothesis Testing. According to the different objectives that were set in Section 3.1, different hypotheses are proposed. Starting from the organisational objectives, the following hypotheses should be tested. • The instrumentation does not alter PTW dynamics and rider driving behaviour. • The instrumentation is appropriate and all required parameters are recorded in a proper manner (no data fail, appropriate accuracy, synchronisation of the different data, etc.). • The data parameters and their accuracy are sufficient to provide a good quantitative and qualitative description of rider behaviour. • The procedure of data storage did not influence the course of the study, and was implemented efficiently. • The methodology for data analysis is appropriate and yields the requested output. • No legal or ethical issues are raised during the study and during data processing. Questions that should be answered are the following: • What are the lessons learned from the naturalistic riding study in respect to the above elements? • What is the most appropriate implementation time schedule for a large NRS? • How could the instrumentation be modified/integrated to improve the observation of riders’ behaviours? • How could other elements of the study (data storage, analysis methodology etc.) be modified/integrated to improve the observation of riders’ behaviours? • Was there a specific issue that was not taken into account which is a prerequisite for the successful implementation of a larger naturalistic riding study? Scientific hypotheses cannot be defined as one is not certain about the results of the study. However, several questions should be considered to achieve the aforementioned scientific objectives. • What rider patterns can be identified by the data? Could these patterns be correlated with specific rider profiles? – This question mainly corresponds to several of the “how” questions mentioned in section1. • How can one define and distinguish between riding under “normal” conditions or riding at conflicts? What are the parameters that one should record and are there specific values that could be set to define conflicts quantitatively? This would also allow setting triggers for conflicts. • What are the contributing factors and dynamic scenarios involved in conflicts? – This will also provide answers to the questions: “How do riders behave and cause an accident?” “How do riders behave to avoid an imminent accident?” and “How do riders behave in order to avoid getting into an accide...
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Hypothesis Testing. ‌ The heritability measuring the genetic sources affecting a phenotype is generally of more concern, and the genetic correlation describing the commonly shared genetic causes between the paired phenotypes is also the parameter of interest. With regard to Formula (4.8) for the computation of ERV, the ERV quantity has a non-zero value when both genetic correlation and heritabilities are non-zero and vice versa. For each pair of phenotypes, testing the null hypothesis H0 : ρ(12) = 0, h2 = 0, or h2 = 0 is the equivalent of assessing the statement of ERV(12) = 0, which gives the null hy- pothesis H0 : ERV(12) = 0 that needs to be examined during the significance testing. Regarding the selection of test statistic, we firstly consider using the LRT statistic by comparing the fit of the null model and that of the alternative model, as stated in Section 3.4.3, with the expression of T(12) = −2 × ΣA(E^RV(12)|Y) − A(E^RV(12)|Y)Σ, where E^RV(12) and E^RV(12) are estimated from the null and alternative models respectively. However, this commonly used LRT statistic is computationally very intensive for moderate to large sample sizes and nearly infeasible for the use of permutation inference. Therefore, we consider to employ the ERV estimator: T(12) = E^RV(12), as an alternative test statistic. The validity of this test statistic will be investigated with simulations in the later section.
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Related to Hypothesis Testing

  • Random Testing Notwithstanding any provisions of the Collective Agreement or any special agreements appended thereto, section 4.6 of the Canadian Model will not be applied by agreement. If applied to a worker dispatched by the Union, it will be applied or deemed to be applied unilaterally by the Employer. The Union retains the right to grieve the legality of any imposition of random testing in accordance with the Grievance Procedure set out in this Collective Agreement.

  • ODUF Testing 6.6.1 Upon request from TWTC, AT&T shall send ODUF test files to TWTC. The Parties agree to review and discuss the ODUF file content and/or format. For testing of usage results, AT&T shall request that TWTC set up a production (live) file. The live test may consist of TWTC’s employees making test calls for the types of services TWTC requests on ODUF. These test calls are logged by TWTC, and the logs are provided to AT&T. These logs will be used to verify the files. Testing will be completed within thirty (30) days from the date on which the initial test file was sent.

  • Human Leukocyte Antigen Testing This plan covers human leukocyte antigen testing for A, B, and DR antigens once per member per lifetime to establish a member’s bone marrow transplantation donor suitability in accordance with R.I. General Law §27-20-36. The testing must be performed in a facility that is: • accredited by the American Association of Blood Banks or its successors; and • licensed under the Clinical Laboratory Improvement Act as it may be amended from time to time. At the time of testing, the person being tested must complete and sign an informed consent form that also authorizes the results of the test to be used for participation in the National Marrow Donor program.

  • Drug Testing (A) The state and the PBA agree to drug testing of employees in accordance with section 112.0455, F.S., the Drug-Free Workplace Act.

  • Substance Abuse Testing The Parties agree that it is in the best interest of all concerned to promote a safe working environment. The Union has no objection to pre-employment substance abuse testing when required by the Employer and further, the Union has no objection to voluntary substance abuse testing to qualify for employment on projects when required by a project owner. The cost and scheduling of such testing shall be paid for and arranged by the Employer. The Union agrees to reimburse the Employer for any failed pre-access Alcohol and Drug test costs.

  • Stability Testing Patheon may be requested to conduct stability testing on the Products in accordance with the protocols set out in the Specifications for the separate fees and during the time periods set out in Schedule C to a Product Agreement. Patheon will not make any changes to these testing protocols without prior written approval from Client. If a confirmed stability test failure occurs, Patheon will notify Client within one Business Day, after which Patheon and Client will jointly determine the proceedings and methods to be undertaken to investigate the cause of the failure, including which party will bear the cost of the investigation. Patheon will not be liable for these costs unless it has failed to perform the Manufacturing Services in accordance with the Specifications, cGMPs, and Applicable Laws. Patheon will give Client ail stability test data and results at Client’s request.

  • Laboratory Testing All laboratories selected by UPS Freight for analyzing Controlled Substances Testing will be HHS certified.

  • Random Drug Testing All employees covered by this Agreement shall be subject to random drug testing in accordance with Appendix D.

  • Meter Testing Company shall provide at least twenty-four (24) hours' notice to Seller prior to any test it may perform on the revenue meters or metering equipment. Seller shall have the right to have a representative present during each such test. Seller may request, and Company shall perform, if requested, tests in addition to the every fifth-year test and Seller shall pay the cost of such tests. Company may, in its sole discretion, perform tests in addition to the fifth year test and Company shall pay the cost of such tests. If any of the revenue meters or metering equipment is found to be inaccurate at any time, as determined by testing in accordance with this Section 10.2 (Meter Testing), Company shall promptly cause such equipment to be made accurate, and the period of inaccuracy, as well as an estimate for correct meter readings, shall be determined in accordance with Section 10.3 (Corrections).

  • Follow-up Testing An employee shall submit to unscheduled follow-up drug and/or alcohol testing if, within the previous 24-month period, the employee voluntarily disclosed drug or alcohol problems, entered into or completed a rehabilitation program for drug or alcohol abuse, failed or refused a preappointment drug test, or was disciplined for violating the provisions of this Agreement and Employer work rules. The Employer may require an employee who is subject to follow-up testing to submit to no more than six unscheduled drug or alcohol tests within any 12 month period.

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