What is the lift of the savings prompt on the outcome metric?

Approximately what is the 95% confidence interval for the control mean? 

In the well-known Fletcher’s band-widening experiments, the bandwidth of noise centered on the frequency of a probe tone was increased. What was found? That the noise bandwidth was unrelated to masking That the amount of masking decreased with increasing bandwidth That he had to increase the level of the noise as its bandwidth increased That the wider the bandwidth, the more masking That the wider the bandwidth, the more masking but only up to a certain bandwidth What is the bandwidth after which there is no change in threshold referred to as?

The organization is planning a future experiment. They calculate that, with 80% power, 5% significance, and their anticipated sample size, the standardized minimum detectable effect is 0.14. If they believe the intervention increases contributions by 10% of the baseline mean, should the experiment be implemented as designed? Hint: you need to use the numbers in Savings Experiment Table 1.

Does this experiment appear balanced?

What output is produced by the below command?   output = smp.tt_ind_test_power( alpha=0.05, nobs1=1000, power =0.90)

Questions 6-8 refer to the following information. levels.fyi is a company that provides job seekers with compensation data. As people negotiate job offers from companies, they can use levels.fyi to see what other job seekers have gotten. For example, someone with a job offer from Meta to be a product manager can see what Meta product managers typically get in compensation. This service is free. levels.fyi also offers a paid negotiation coaching service which costs $1000. Only about 1% of their users actually pay for this service, and levels would like to increase this share. They ran an experiment offering a discounted price of $500 to a random subset of users. Given their prices and costs, levels.fyi determined that they would want to lower the price for everyone, if the lower price caused an increase in take-up of coaching of at least 0.04 on average. Some data from the experiment are in the table below:   Group Sample size Coaching  take-up average Coaching take-up standard deviation Control ($1000 price) 1,225 0.011 0.10 Treatment ($500 price) 1,225 0.020 0.17

A person of below-median age in the treatment arm has a value of the outcome metric of 25. After demeaning by the subgroup mean, what would be her value?

An organization conducts an A/B test with adequate power. Upon analyzing the data, they find that condition B performs statistically significantly better than condition A. What of the following would be most important for them to consider before deciding whether to scale up the intervention?

Does this experiment appear balanced?