The dataframe for your team is called your_team_df. The variable 'pts' represents the points scored by your team. Calculate and print the mean points scored by your team during the years you picked. Identify the mean score under the null hypothesis. You only have to identify this value and do not have to print it. (Hint: this is given in the problem statement) Assuming that the population standard deviation is unknown, use Python methods to carry out the hypothesis test. Calculate and print the test statistic rounded to two decimal places. Calculate and print the P-value rounded to four decimal places.

Write a function so that the main program below can be replaced by the simpler code that calls function original main program: miles_per_hour = float( minutes_traveled = float( hours_traveled = minutes_traveled / 60.0 miles_traveled = hours_traveled * miles_per_hour print('miles: %f' % miles_traveled) sample output with inputs: 70.0 100.0 miles: 116.666667

Usually, when we sniff packets, we are only interested certain types of packets. we can do that by setting filters in sniffing. scapy’s filter use the bpf (berkeley packet filter) syntax; you can find the bpf manual from the internet. set the following filters and demonstrate your sniffer program again (each filter should be set separately): (a) capture only the icmp packet. (b) capture any tcp packet that comes from a particular ip and with a destination port number 23. (c) capture packets comes from or to go to a particular subnet. you can pick any subnet, such as 128.230.0.0/16; you should not pick the subnet that your vm is attached to.

In he example code, what does the title attribute create? a tool tip an element a source a markup