The central limit theorem implies select one: a. the distribution of a large population is approximately normal. b. the distribution of the average of a sample from a large population is approximately normal. c. the distribution of a large sample is approximately normal. d. the distribution of the average of a large sample is approximately normal.

d. the distribution of the average of a large sample is approximately normal.

Explanation:

The Central Limit Theorem refers to the convergence of sums of random variables for a normal distribution. Given its importance in theory and applications, this theorem is considered the most elementary probability theorem. According to the Central Limit Theorem, when the sample size is large enough, the mean distribution is an approximately normal distribution. The theorem applies regardless of the form of population distribution. This is a theorem of great importance to data science because many common statistical procedures require that the data be approximately normal.

if interdependence implies a two-way dependence, and if each partner is equally dependent on the other for success, then there is an equal commitment to the making the partnership successful. the advantage is sustainability of the relationship, the disadvantage is that decisions are "democratic" and therefore may take longer to reach and more likely to be a compromise (which is not always the best solution). as the interdependence moves away from equality, the decisions become more influenced by the more independent partner. in the extreme the relationship becomes more dictatorial and more like "master-slave". generally the relationship has less commitment in both directions and is more likely to be temporary.

if one generalizes (and one shouldn't), equity partnerships, which is probably what is implied by interdependence, can be slow to progress or change but durable. the extreme alternative, independent-dependent partnerships tend to be efficient but more fragile.

hope this but you will have to site your own evidence. : )

the earthquake in haiti was a magnitude of 7.0 according to the u.s geological survey yet the smaller earthquake in haiti killed more than 200,000 and left more than 1.2 million people homeless. the chile earthquake was a magnitude of 8.8 and 500 times more stronger but chile's earthquake only injured 712 people.