resultant

Examples of resultant in the following topics:

• Results

  • The results section of a scientific paper objectively presents the empirical data collected in a study.
  • The results section is where you state the outcome of your experiments.
  • Think of the results section as the cold, hard facts.
  • Simply say, "The results were not found to be statistically significant," or "The results supported the hypothesis, with $p < .05$ significance," or the like.
  • It will be tempting to start drawing conclusions as you write the results section.

• Superposition of Fields

  • The resultant of multiple electric fields acting on the same point is the sum of the strength of each field's applied force at that point.
  • For example, if forces A and B are constant and simultaneously act upon an object, illustrated as O in , the resultant force will be the sum of forces A and B.
  • Vector addition is commutative, so whether adding A to B or B to A makes no difference on the resultant vector; this is also the case for subtraction of vectors.
  • An overall resultant vector can be found by using the Pythagorean theorem to find the resultant (the hypotenuse of the triangle created with applied forces as legs) and the angle with respect to a given axis by equating the inverse tangent of the angle to the ratio of the forces of the adjacent and opposite legs.
  • Their sum is commutative, and results in a resultant vector c.

• Overview of the IMRAD Model

  • The results section should describe your results without discussing their significance, while the discussion section should analyze your results without reporting any new findings.
  • You will analyze your results in the next section.
  • If you find some results that don't support your hypothesis, don't omit them.
  • Report incongruous results, and then address them in the discussion section.
  • If you find that you need more background information to provide context for your results, don't include it in the results section—go back and add it to your introduction.

• Smallpox in Boston, 1721

  • Each case represents one person with two variables: inoculated and result.
  • The variable result has outcomes lived or died.
  • How does this result compare with the result of Exercise 2.44?
  • 2.44:P(result = died | inoculated = no) = P(result = died and inoculated = no)/P(inoculated = no) = 0.1356/0.9608= 0.1411.
  • 2.45: P(result = died | inoculated = yes) = P(result = died and inoculated = yes) P(inoculated = yes)= 0.0010/0.0392 = 0.0255.

• Discussion and Conclusion

  • The discussion section of a scientific paper should interpret the results of your research.
  • Then explain the results themselves.
  • Discuss how they fit (or do not fit) your hypothesis, and whether they are consistent with the results of similar research projects.
  • Acknowledge other possible interpretations of your results, and admit your project's limitations.
  • It should take one to three paragraphs to restate the research question, the main results, and the meaning of those results.

• Creating a Hypothesis Test

  • Decide on an appropriate level of significance for assessing results.
  • Conventional levels are 5% ($\text{sig}<0.05$, meaning that results have a probability under the null hypothesis of less than 1 time in 20) or 1% ($\text{sig}<0.01$, meaning that results have a probability under the null hypothesis of less than 1 time in 100).
  • Thus, one-tailed tests are appropriate when testing that results will only be higher or smaller than null results, or when the only interest is on interventions which will result in higher or smaller outputs.
  • $p$-values can be interpreted as the probability of getting the observed or more extreme results under the null hypothesis (e.g., $p=0.033$ means that 3.3 times in 100, or 1 time in 33, we will obtain the same or more extreme results as normal [or random] fluctuation under the null).
  • Significant results can also be reported in the line of "without the treatment I administered, experimental results as extreme as the ones I obtained would occur only about 3 times in 1000.

• Getting started

  • Verify and review the results.
  • Discuss the results.
  • After agreeing on goals and objectives, set a date for the next audit and review the results.
  • (Scott, Jonathan T., Managing the New Frontiers) Just don't fall into the trap of placing more time and effort into creating measurement statistics than performance results.

• Extent of Host Involvement

  • Infectious diseases result from the interplay between the pathogens and the defenses of the hosts they infect.
  • The appearance and severity of disease resulting from the presence of any pathogen depends upon the ability of that pathogen to damage the host as well as the ability of the host to resist the pathogen.
  • Primary pathogens cause disease as a result of their presence or activity within the normal, healthy host, and their intrinsic virulence is, in part, a necessary consequence of their need to reproduce and spread.
  • Opportunistic diseases may be caused by microbes that are ordinarily in contact with the host, such as pathogenic bacteria or fungi in the gastrointestinal or the upper respiratory tract, and they may also result from (otherwise innocuous) microbes acquired from other hosts or from the environment as a result of traumatic introduction.
  • An opportunistic disease requires impairment of host defenses, which may occur as a result of several factors such as genetic defects, exposure to antimicrobial drugs or immunosuppressive chemicals, exposure to ionizing radiation, or as a result of an infectious disease with immunosuppressive activity.

• Was the Result Important?

  • The results are deemed important if they change the effects of an event.
  • When used in statistics, the word significant does not mean important or meaningful, as it does in everyday speech; with sufficient data, a statistically significant result may be very small in magnitude.
  • Such results are informally referred to as 'statistically significant (at the $p=0.05$ level, etc.)'.
  • Researchers focusing solely on whether individual test results are significant or not may miss important response patterns which individually fall under the threshold set for tests of significance.

• Reasons for and Consequences of Shifts in the Aggregate Demand Curve

  • An increase in any of the four inputs into AD will result in higher real output or an increase in prices.
  • For example, an increase in total expenditures will result in a shift rightwards, while a decrease in expenditure will result in a shift to the left.
  • As noted above, any increase in the overall AD will result in an outwards (right-ward) shift of the AD curve.
  • However, different levels of economic activity will result in different combinations of output and price increases.
  • is useful for understanding the distribution between price increases and output increases that will result in a given economy when AD increases.