Question

1. Describes what is involved in determining

   1. if a research questionnaire is valid and reliable?

   2. if a selected sample distribution is appropriate?

Answer 1

Solution:

1. The legitimacy of an exploration instrument, for example, a questionnaire is commonly controlled by leading an observation or exploring study on a little example with comparative pattern qualities (yet not a similar report test). This will give you the chance to make alterations and changes to the questionnaire things with the goal that the things will properly gauge issues they are intended to quantify.

2. These rundowns are the different types of legitimacy going from the most minimal to the most astounding level. To start with, comprehend legitimacy as the degree as well as the capacity of a scale/measure to gauge what it is expected to quantify.

Face legitimacy speaks to the most straightforward or the least logical type of legitimacy and it depends on the regularizing judgment of the scientist to see whether the scale estimates what it professes to quantify.

Content legitimacy is progressively logical in light of the fact that the scientist goes past minor worth decisions and ensures all estimation gadgets give sufficient inclusion of the analytical inquiries.

Foundation legitimacy is worried about how the measure or the scale concurs or associates with other standard proportions of similar development. For instance, how does the educator's task of an understudy's insight concurs with the understudy's IQ test outcomes?

Simultaneous legitimacy is a type of paradigm legitimacy which exhibits when scores acquired from another measure are straightforwardly identified with scores from an increasingly settled proportion of similar factors. See likewise prescient legitimacy.

For sampling distribution:

1. If the population is skewed, then the sample mean won't be normal for when N is small. ...
2. If the population is normal, then the distribution of sample mean looks normal even if N = 2.
3. If the population is skewed, then the distribution of sample mean looks more and more normal when N gets larger.