1. You will find your data set with this assignment. This data set was created in MATH class and will be considered a random sample of all MATH students.Open this data set in Minitab.
2. It is always a good idea to review your data set for extreme values that might be suspicious.These extreme values can be due to typing errors during data entry or might be legitimate. If we identified an outlier, it might be possible to investigate each specific outlier to see if that person really exists.
3. Generate a column of Pulse Differences (AEPL - BEPL) using the Calc function in Minitab.This will provide the change in pulse after 1 minute of exercise.
4. Hunt Outliners: Create boxplots of all the variables [Height, Weight, BMI, Before Exercise Pulse (BEPL), After Exercise Pulse (BEPL), and Pulse Differences]. If the boxplots are difficult to interpret, you can also examine the summary statistics for these variables (descriptive statistics).You do not need to include this information (boxplots and summary statistics) with your submission, unless you choose to do so for illustration purposes, but you should use them to identify any unusual data or outliers.
5. If there are any outliers, we won't be able to identify and investigate the specific person in the data.That is what we would attempt to do if the entries were not anonymous. However, examine those outliers or unusual data and decide whether or not these subjects are legitimate or should be removed entirely from the data.Use some common sense.For example, do you expect someone to have a higher before-exercise pulse than an after-exercise pulse? Would you expect to find someone in the data that is 10 feet tall?Remember, if you decide to remove someone, justify your decision. There should be some basis in fact for the removal other than your opinion.

You should note any outliers and the entries you have deleted. Make sure you discuss which entries were removed and why they were removed.

1. Your data is now cleaned and ready for analysis.
2. Before you move on to answering the questions, create two visual representations for this data sets (a bar chart and a histogram of your choice!)

Questions

Assume that the data set we are using represents a random sample of all MATH students.Further, assume that the populations are normally distributed (they are). That way we don't have to worry about normal probability plots if any of our samples are below 25.Thus, we will be basing our inference and conclusions on the population of MATH students.

For the following questions, you must outline your methodology, and state your research question first, followed by your answer to the question. You can then quickly discuss your methodology and provide the Minitab output as a backup for your analysis and conclusions.

Questions (Any testing or inference should be done at 95% Confidence):

1. It is claimed that females have a lower mean pulse rate in general (BEPL) than men. Given this data set, do females have a lower mean before exercise pulse rate (BEPL) than men? (Note:Minitab will put females in the first column and males in the second column if you use samples in one column with subscripts)
2. It is claimed that due to smaller lung capacity, a female's heart must beat faster during exercise.Given this information, do females have a higher mean after exercise pulse rate (AEPL) than men?Perform this test at a 95% level of confidence. (Note:Minitab will put females in the first column and males in the second column if you use samples in one column with subscripts)
3. It is claimed that one minute of exercise will increase a typical person's pulse (mean pulse difference) by more than 30 beats per minute.At a 95% level of confidence, evaluate this objective.
4. It is your turn to use the data! You will need to come up with another research question to be answered by this data set. Put down your question, and use the right statistical analysis to answer it.

Data

User_type	Gender	Height	Weight	BMI	BEPL	AEPL
student	female	66	160	25.82	65	97
student	female	62	140	25.6	102	120
student	male	70	180	25.82	61	102
student	female	67	145	22.71	82	123
student	male	72	185	25.09	86	110
student	male	70	140	20.09	98	120
student	female	65	140	23.29	73	80
student	male	74	165	21.18	70	95
student	male	66.5	145	23.05	96	118
student	female	62	130	23.77	83	100
student	male	72	185	25.09	82	102
student	male	73.5	195	25.38	80	132
student	male	68	135	20.52	95	126
student	female	64	130	22.31	66	91
student	male	71	242	33.75	78	96
student	male	71	240	33.47	75	121
student	male	74	175	22.47	86	118
student	female	67	150	23.49	71	94
student	male	71	180	25.1	61	80
student	male	71	225	31.38	62	80
student	male	74	185	23.75	65	86
student	female	63	125	22.14	106	120
student	female	62	125	22.86	70	90
student	female	63	150	26.57	87	88
student	female	64.8	145	24.28	77	82
student	female	68	135	20.52	55	97
student	male	71	144	20.08	55	99
student	female	69	140	20.67	88	115
student	female	69	140	20.67	110	135
student	female	65	145	24.13	76	124
student	female	63	120	21.25	93	131
student	male	65	157	26.12	91	113
student	female	68	180	27.37	80	110
student	female	68	145	22.04	82	105
student	female	67	140	21.92	97	110
student	male	71	300	41.84	50	89
student	male	71	165	23.01	50	86
student	male	75	170	21.25	110	146
student	female	66	150	24.21	90	112
student	female	64	120	20.6	84	62
student	female	66	140	22.59	78	130
student	male	71	175	24.4	87	92
student	male	72	185	25.09	70	100
student	male	74	207	26.57	68	91
student	female	65	135	22.46	90	96
student	female	64	135	23.17	115	146
student	male	74	202	25.93	72	99
student	male	68	130	19.76	88	114
student	male	70.1	155	22.17	81	102
student	male	76	210	25.56	99	112
student	male	70	173	24.82	79	104
student	female	66	135	21.79	76	89
student	male	74	179	22.98	58	72
student	female	64	136	23	70	100
student	female	62	112	21.5	68	74
student	female	69	140	20.8	62	110
student	female	65	139	23.1	60	130
student	female	62	120	21.9	62	88
student	female	61	118	22.3	60	102