A group of researchers is designing an experiment to test whether an herbal supplement will help people lose weight. The researchers selected a sample of 500 adults who want to lose weight, and over the next four months, 250 of them will take the herbal supplement daily whereas the remaining 250 will take a placebo daily. At the end of the four months, the researchers will compare the weight loss for the two groups.
Why is it important that the researchers use randomization to assign each of the adults who want to lose weight to a treatment group?

Randomization removes lurking variables and biases.

Step-by-step explanation:

In case of an experimental design the groups are divided randomly.

Randomization is important so that there are no bias present in the study and to control any lurking variables. The controlling of the lurking variables provides an accurate result.

Lurking variables have a significant effect on the response variable. Presence of lurking variables can indicate a strong relation between variables or conceal any true relation between the variables.

Randomization thus gets rid of lurking variables and biases.

Also if randomization is used then each of the groups are similar in every way other than the fact that each group is provided with different treatment.

n

step-by-step explanation:

x > 1.3

step by step:

8.5−0.9x> 9.8−1.9x

step 1: simplify both sides of the inequality.

−0.9x+8.5> −1.9x+9.8

step 2: add 1.9x to both sides.

−0.9x+8.5+1.9x> −1.9x+9.8+1.9x

1x+8.5> 9.8

step 3: subtract 8.5 from both sides.

1x+8.5−8.5> 9.8−8.5

1x> 1.3

step 4: divide both sides by 1.

1x/1 > 1.3/1