The purpose of a dichotomous key is to identify organisms
Explanation:
A dichotomous key is a kind of a tool that guides to classify and identify different organisms.
This key as the name indicates - dichotomous- consists of two parts or options to identify a species.
The method utilizes a series of questions/answers with two possible outcomes.
Taxonomically, a dichotomous key is used to basically identify a species or an organism by its scientific name.
All of the natural elements like the plants, animals, birds, etc are identified using this key.
Types of dichotomous key includes nested, linked, branching tree etc.
They use radiometry and pyrometry
NASA uses the Transiting Exoplanet Survey Satelite (TESS) telescope that employes this technology
This telescope measures the brightness/luminosity of stars. When this brightness drops regularly, every more or less in the same number of years, then there is the likelihood of a planet orbiting the star. The dip in brightness of the star is directly proportional to the size of the planet and the distance between the star and the orbiting planet.
Answer:
Option 4
Explanation:
Folate is vitamin B and occurs naturally in various food items such as green leafy vegetable, lentils, peas, beans, in fruits such as banana, melon, and enriched products such as bread, juices etc. Folate is essential for making up genetic material or DNA. Out of all given options, option 4 has both lentil and spinach (green leaves) which are rich source of folate. Option 1 has bread as a source of folate. Hence, the correct answer is option 4.
Answer:
It is necessary to make the following assumptions when making inferences about a group of people based on a sample of subjects drawn from that group:
- Data is quantitative in nature.
- A sample size of 30 or more is required.
- The data set must consist of a simple random sample.
- A Normal Distribution must be present in the data.
The data must come from a sample that isn't all the same size so that it can be generalized well.
The sample size must be at least 30 or more, according to the central limit theorem.
Mean and standard deviation are two examples of quantitative data from which statistical conclusions can be drawn.
To avoid bias, the sample size should be increased rather than the distribution skewed.
Explanation:
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