To avoid the cost of sending out coupons you do not need to, you ask the data science team to plan an experiment just large enough (with just enough statistical power) to reliably detect a treatment effect if the true effect on those who open the mail and realize they have the coupon is a $2 increase in revenue over the next year. the data science team tells you that an experiment with 100,000 people in the treatment group (leaving the remaining 900,000 in the control group) will be well-powered to detect an overall difference between the entire treatment and control groups of $2 in revenue over the next year. to send out the minimum number of coupons required while still having enough statistical power to detect a $2 effect of opening the mail, can you send out fewer, the same number of, or more coupons than 100,000? [5 points]