Adigitized video transmission carries a randomly mixed set of video packets. the occurrence statistics of the packets are designated in 10 groups. the video-transmission involves streaming of packets wherein the statistics of occurrence of bit rate may depend strongly on bit-rate values in consequent packets streamed and the rv is considered as of variable bit rate (vbr) type the number of occurrences of each group and the corresponding random value of the associated random bit rates in the packets (rvs) are as follows events enumerated bit rate (r) video in mbps: rv 6.4 5.9 0.6 6.2 5.76.1 6.35.7 5.6 0.2 packets number of 80 | 60 | 50 | 40 | 50 | 60 | 75 40 30 20 occurrences determine the following of the rv (bit rate -r) find the upper and lower bounds of the average performance of the rv state with reason the most appropriate mean value (am him or gm) that describes the average performance of the bit rate i. ? . iii. find the expected mean, median, mode, variance and standard deviation iv. plot the cumulative probability distribution (cdf) of the rv. answer-hints: median 5.8: ? = 1.9431

Your task this week is to write a very simple spam classifier in python. it will classify messages as either spam (unwanted) or ham (wanted). the program will have a set of spam_words, words that are known to appear in spam messages. that set is included in the template file spam. pypreview the document. you will also define a spam threshold which reflects the allowed percentage of spam words in the message. you'll compute a 'spam indicator', which is the ratio of spam words to the total number of unique words in the message. if the spam indicator exceeds the spam threshold, the message is classified as spam. otherwise it is classified as ham. we'll assume that the spam threshold is a constant and has a value of 0.10. your program will prompt the user for a message and then will print the corresponding spam indicator with two decimal digits and the corresponding classification (spam or ham). the program will be case insensitive. the spam words are detected whether they are in lower case or upper case or mixed case. each word, spam or not, is counted once (even if it appears multiple times in the message.) the program will remove punctuation from the message before identifying the words and computing the spam indicator. for example '! ' must be identified as the spam word 'now'.

The graph shows median weekly earnings for full-time workers according to education level. which can you not conclude?

Worth 50 points answer them bc i am not sure if i am wrong