SPSS300822/INFO1110

Monday, September 5

Overview of the Research Topic

NOTE: While you may use some of the sources listed below, your report must be your own work and should not copy the information provided below.
Here is a brief overview/background to the research topic.
Across continents men eat more meat than do women, exhibit more favourable attitudes towards meat consumption, and are less likely to be vegan or vegetarian (Adams, 1990; Rotherberger, 2013). Meat also has specific nutritional benefits for men, containing creatine and other amino acids, which are key for muscle strength and development (Bonjour, 2005). Body fat, on the other hand, is critically important for female health and the developmental health of a mother's pre-natal and neo-natal baby (Jayasinghe et al., 2008; Innis, 2007). Fat storage on the body (especially easily metabolisable gluteal fat), is strongly promoted by a high carbohydrate diet (Mente et al., 2009).
These sex differences in nutritional requirements are thought to have led to sex differences in psychological responses to food (Love & Sulikowski, 2018). This has been demonstrated in visual search tasks and other attention tasks where images that are highly relevant to individuals capture attention more readily than low relevance stimuli. In visual displays containing various food items, men detect and respond more quickly to images of meat than to non-meat, while women make more careful decisions when asked to search for non-meat foods (taking longer to decide the food item is absent, minimising the chances that they will miss it), compared to meat foods (Love & Sulikowski, 2018).
The same study also suggested that increased hunger levels led to men responding even more quickly to meat, and women to non-meat foods. Also, hunger led to women responding even more carefully to non-meat foods, and men more carefully to meat foods. Although a lack of power meant that the effects of hunger were statistically equivocal. Therefore, the current study was designed to expand on these findings by investigating whether men (but not women) responded faster to meat when they were hungry compared to not hungry, and whether women (but not men) responded faster to nonmeat (carbohydrate based) foods when they were hungry compared to not hungry.
References
Adams, C. (1990). The Sexual Politics of Meat: A Feminist Vegetarian Critical Theory. New York, NY: Continuum International Publishing Group.
Bonjour, J.P. (2005). Dietary protein: an essential nutrient for bone health. J. Am. Coll. Nutr. 24, 526S–536S.
Innis, S. M. (2007). Human milk: maternal dietary lipids and infant development. Proc. Nutr. Soc. 66, 397–404.
Jayasinghe, Y., Grover, S., and Zacharin, M. (2008). Current concepts in bone and reproductive health in adolescents with anorexia nervosa. BJOG 115, 304–315.
Love, H. and Sulikowski, D. (2018). Of meat and men: Sex differences in implicit and explicit attitudes toward meat. Frontiers in Psychology, 9, 10.3389/psyg.2018.00559.
Mente, A., de Koning, L., Shannon, H. S., and Anand, S. S. (2009). A systematic review of the evidence supporting a causal link between dietary factors and coronary heart disease. Arch. Intern. Med. 169, 659–669.
Rothberger, H. (2013). Real men don’t eat (vegetable) quiche: masculinity and the justification of meat consumption. Psychol. Men Masc. 14, 363–375.

Where to start: Searching the literature

We have created an assessment 3 starter readings folder in the subject Leganto list (via “readings and resources” on the subject site).
You should begin by reading the Love & Sulikowski (2018) article in the list.
Love, H. and Sulikowski, D. (2018). Of meat and men: Sex differences in implicit and explicit attitudes toward meat. Frontiers in Psychology, 9, 10.3389/psyg.2018.00559.

The experiment in the research report that you will be writing is based on this research by Love and Sulikowski. It will therefore be very important for you to discuss this research in your report, to help justify why you carried out your experiment.

Once you have read that article, read the other articles in the Leganto list. These articles will provide further background on the topic and give you some ideas for keywords and other articles.

Some tips for identifying relevant articles include:
⦁ have a look at the reference list of articles and search for those sources
⦁ look at the keywords used in articles and use similar keywords in your search
⦁ in Google scholar, you can use the “cited by” function to look for articles that have cited these studies (this usually leads to similar research)
⦁ in Google scholar, the “related articles” function will help you search for similar articles
⦁ quite often researchers will publish multiple articles on the same topic, so you may find it helpful to search the authors of articles to find related works or collaborators
⦁ the CSU library website has many useful tutorials and help guides for developing your research skills (e.g., search strategies): https://library.csu.edu.au/for-study
⦁ there is not a huge amount of literature on this topic, so you will need to get creative with your searching and look for studies relating to cognition (e.g., attention) and diet/health.
Who were the participants?
The table below provides information about the number and age of males and females that participated in the study. Please do not copy this table directly into your report. This information needs to be presented in APA format in your report.
Males Females
N 124 416
Age range 18-83 17-61
Mean age 32.6 31.8
Age standard deviation 12 10.5

The participants were recruited from 2 different sources:
⦁ Biopsychology students enrolled on-campus or online at CSU on the Bathurst, Wagga Wagga, and Port Macquarie campuses. These participants received invites via subject announcements.
⦁ 1st year psychology students at CSU in the SONA participant pool. These participants received invites and links to the study via the SONA website.
How participants completed the study
Part 1: Online Survey
Participants completed the online survey in the Qualtrics survey platform.
Please see the online survey questions in the assessment 3 folder. The online survey contained questions relating to participant demographics (e.g., age, gender) as well as dietary habits (e.g. types of foods they eat), and current hunger levels.
On average, this survey took about 10 minutes to complete.
Part 2: Visual Search Task
Participants completed a visual search task in the Inquisit reaction time platform.
On average, the visual search task took about 20 minutes to complete.
Please see examples of the visual search task stimuli in the assessment 3 folder. You may wish to include these examples in your appendix of your report.

Participants were presented with visual arrays like the one above, that contained 9 images on the screen. Participants were instructed to look for pictures of particular types of food in each visual array, amongst the distractor images. In the example above, participants were instructed to look for a picture of Pasta.
There were 11 blocks within the visual search task. That is, each block had instructions for participants to look for a different food type. There were 5 meat food types blocks (red meat, white meat, processed meat, fish, other seafood) and 6 nonmeat blocks for (carbohydrate) food types (bread, pasta, fruit, starchy vegetables, sweet snacks, and savory snacks).
In each of the 11 blocks, there were 18 trials. That is, for each food type, there were 18 visual arrays (like the picture above) that participants had to search for the food type in.
Not every trial contained pictures of the food type. Some visual arrays only contained distractor images. Therefore, in each trial, the participant was instructed to search for the food item amongst distractors. If the food type was present in any of the 9 images in the visual array, the participant needed to press P. If the food type was not present in the array, they needed to press A. Participants were instructed to make these decisions as fast and accurate as possible. It was a reaction time in making these decisions that was our dependent variable in this study and what we were interested in measuring (i.e., Whether people responded faster to meat or nonmeat images).

Data Analysis and Understanding the Results

For those of you that have never done statistics before, or are very new to statistics, DON’T PANIC! We have done the hard bit for you and run the analyses on the data. In the following sections, we will work through the data and what it means so that you can use it for your research report.
NOTE: For those of you that have done statistics, please note that we will not be reporting/considering assumption testing for this assessment. There are some students who have not yet completed statistics subjects, and so we are keeping this assignment nice and simple.
How the Data Was Analysed

Survey data from Qualtrics and reaction time data from Inquisit were collated in an Excel spreadsheet. We then carried out statistical analyses using IBM SPSS Version 28.

The food types we considered for the analysis were the 5 meat foods (red meat, white meat, fish, seafood, and processed meats) and the 6 carbohydrate foods (bread, pasta, fruit, starchy vegetables, savory snacks and sweet snacks).
The first thing we did was work out every participant’s mean response time to locate each food type. To do this we considered only trials where the food target was present, and only trials where the participant responded correctly. Their response times to these trials were then averaged to give us a mean response time for each food type for each participant.
We then averaged these means for the 5 meat foods and the 6 carbohydrate foods for each participant.
So, our data set looked something like this (each mean is in ms, where 1000ms = 1s):
Participant Sex Meat Foods Non-meat foods Hunger level
1 M 847.54 946.39 9
2 F 1180.07 1160.68 4
3 F 606.50 664.10 5
4 M 1014.56 891.22 8
: : : :
: : : :
62 F 783.98 725.34 6

Analyzing the data – were our hypotheses supported?
Remember we have 2 hypotheses, one for men and one for women. These were:
⦁ For men, we predict a negative correlation between response times to meat foods and self-reported hunger levels (as men get hungrier, their response times to meat foods get faster).
⦁ For women, we predict a negative correlation between response times to non-meat (carbohydrates) foods and self-reported hunger levels (as women get hungrier, their response times to non-meat foods get faster).
Our statistical analyses below will test whether our hypotheses were supported or not.


Correlations
Before drawing any conclusions about what our data are telling us, we need to conduct some statistical tests. These tests will tell us whether any of the relationships between our variables are statistically reliable (usually termed statistically significant).
The type of analyses we will conduct are called Pearson correlation analyses.
The following websites provides an overview of correlations:
⦁ https://www.simplypsychology.org/correlation.html
⦁ https://www.youtube.com/watch?v=dsyTQNUvqH0
⦁ https://www.statisticshowto.com/probability-and-statistics/correlation-coefficient-formula/
We have also placed some statistics textbooks in the Leganto list for further information.
Below is the correlation output from SPSS. You are NOT permitted to copy/paste this table directly into your research report. You will need to determine which information from this table to include in your report and write your results in APA 7th format.

NOTE: mean RT refers to “mean reaction time” or speed of responses in the visual array task (i.e., how fast males and females responded to images of meat or carbs).
Is it significant? Interpreting the statistics.
To work out whether a correlation is statistically significant (to determine whether our hypothesis was supported or not), we need to look at the p-value. The p-value (for all statistical tests, not just a correlation), is the probability that you would observe an effect at least as large the one you did observe, even if there was no actual effect in the real world. For example, if a p-value is .323, this means that if there is no effect, we would still see a difference as large as the one we did just over 30% of the time in studies like ours. That’s not rare enough to conclude that our data is “statistically significant”. Only when an effect would be seen less than 5% of the time (i.e., p < .05) if it didn’t actually exist in the real world, do we decide that it was sufficiently unlikely to have occurred under those circumstances. In those cases, we conclude that the most likely explanation is that the effect does exist in the real world, and that is when we label it statistically significant.
Effect size
Effect size refers to the magnitude of the effect: a larger correlation represents a larger effect. For more information, please see this link: https://www.simplypsychology.org/effect-size.html
With a Pearson correlation, you have the correlation coefficient (r) that tells you the strength of the relationship between the variables, the p-value that tells you the statistical significance of the effect, and the effect size that tells you the magnitude of the effect. In your report, you should include all 3 of these when reporting your findings.

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INFO1110

Assignment Description
Your Personalized Workout Program
Your task is to create a program for your local gym to assess their members' needs and give them exercises based on their situations and goals. Your program decides the best exercise for each member and gives them detailed instructions to run the exercise.

First task
These are workouts categories based on member's sex and age and also based on their goals:

Gym workout for fat loss

Gym workout for stretch and relax

Gym workout for high-intensity exercises

Gym workout for strong legs

Gym workout for strong ABS

Gym workout for strong shoulders and arms

Gym workout for a male younger than 18 years old

Gym workout for a female younger than 18 years old

Gym workout for a male at least 18 years old

Gym workout for a female at least 18 years old

Each one of these categories has a name (e.g. "Gym workout for fat loss") and a list of exercises, repetitions/minutes, and sets for each exercise. The following is a set of exercises for the workout category "Gym workout for fat loss":

Gym workout for fat loss

Plate thrusters (15 reps x 3 sets)
Mountain climbers (20 reps x 3 sets)
Box jumps (10 reps x 3 sets)
Lounges (10 reps x 3 sets)
Renegade rows (10 reps x 3 sets)
Press ups (15 reps x 3 sets)
Treadmill (15 mins x 2 sets)
Supermans (15 reps x 3 sets)
Crunches (20 reps x 3 sets)

These ten categories of workouts and their detailed exercises are in readme.md file. Please make your categories according to them, and avoid making typo and punctuation mistakes.

Second task
In this part of your code, you are asking members to answer some questions about themselves. The questions you are asking are based on their name, sex, age, goals for exercising, and how many days per week they can exercise. These questions should help the program decide what sort of exercises suit the member better. Here is the set of questions to ask:

Please enter your name:

Please enter your age:

Please enter your biological sex (female/male):

What do you want to get out of your training?
1. Your goal is losing weight
2. Your goal is to staying calm and relax
3. Your goal is increasing your heart rate
4. Your goal is having stronger legs
5. Your goal is having stronger ABS
6. Your goal is having stronger shoulders and arms
Choose a number between 1 to 6:

How many days per week you can train:


Third task
The program should decide what exercise suits each member based on their input. Here you will need to loop through the workout categories based on members' age/sex or goals. Depending on how many days per week they want to train, choose one workout from the list of goals (workout 1 to 6) and one workout from the list of age/sex (workout 7 to 10) alternatively, and repeat it for the rest of the week. The first workout is always from category [1-6] and the second workout is from categories [7-10].

For example, let's say our member's name is "Lucas", a 19 years old male whose goal is to lose weight and can train 2 days a week. Your program should give them two sets of workouts, one from the category based on their goal, and another from the category based on their age/sex:

Day 1: Gym workout for fat loss

Day 2: Gym workout for a male at least 18 years old

If he can only train one day a week, the program only chooses from the goal category for him. For example:

Day 1: Gym workout for fat loss

If he can train three days a week, the program will repeat between the two categories, starting from the goal category. For example:

Day 1: Gym workout for fat loss

Day 2: Gym workout for a male at least 18 years old

Day 3: Gym workout for fat loss

The format of the output shown to the user is as follows. This is generated for "Lucas," who is 19 years old male and can train 1 day a week:

Hello Lucas! Here is your training:
-------------------------------------------------------------------------------------
Day 1
Gym workout for fat loss

Plate thrusters (15 reps x 3 sets)
Mountain climbers (20 reps x 3 sets)
Box jumps (10 reps x 3 sets)
Lounges (10 reps x 3 sets)
Renegade rows (10 reps x 3 sets)
Press ups (15 reps x 3 sets)
Treadmill (15 mins x 2 sets)
Supermans (15 reps x 3 sets)
Crunches (20 reps x 3 sets)
-------------------------------------------------------------------------------------



Fourth task
Your last task is to adjust the intensity of the workouts based on members' age. Your program has to check members' age and lower the intensity of the workouts for older people by lowering the number of reps/mins for each exercise. The reps/mins are lowered based on the following rules:

For ages above 60 years old, the program lowers the reps/mins by 1% for every year above 60 years old.

For ages above 65 years old, the program lowers the reps/mins by 5% plus 2% for every year above 65 years old.

For ages above 75 years old, the program lowers the reps/mins by 25% plus 3% for every year above 75 years old.

For ages above 80 years old, the program lowers the reps/mins by 40% plus 4% for every year above 80 years old, up to a maximum of 80%.

The number of reps/mins should be rounded up to the nearest whole integer, and it cannot be less than 1.

Hint: Use math.ceil() to round numbers to the nearest whole integers.

End of Program
Always print Bye <name>. at the end of the program, where <name> is the name entered.

Program Executions
Your program start working by running this command:

$ python3 gym.py
Here is an example of executing your program when it's working without an error, where # denotes user input:

$ python3 gym.py
Please enter your name: #Lucas

Please enter your age: #19

Please enter your biological sex (female/male): #male

What do you want to get out of your training?
1. Your goal is losing weight
2. Your goal is to staying calm and relax
3. Your goal is increasing your heart rate
4. Your goal is having stronger legs
5. Your goal is having stronger ABS
6. Your goal is having stronger shoulders and arms
Choose a number between 1 to 6: #1

How many days per week you can train: #2

Hello Lucas! Here is your training:
-------------------------------------------------------------------------------------
Day 1
Gym workout for fat loss

Plate thrusters (15 reps x 3 sets)
Mountain climbers (20 reps x 3 sets)
Box jumps (10 reps x 3 sets)
Lounges (10 reps x 3 sets)
Renegade rows (10 reps x 3 sets)
Press ups (15 reps x 3 sets)
Treadmill (15 mins x 2 sets)
Supermans (15 reps x 3 sets)
Crunches (20 reps x 3 sets)
-------------------------------------------------------------------------------------
Day 2
Gym workout for a male at least 18 years old

Standing biceps curls (20 reps x 3 sets)
Seated incline curls (18 reps x 3 sets)
Seated dumbbell presses (12 reps x 3 sets)
Leg presses (15 reps x 3 sets)
Bench presses (10 reps x 4 sets)
Tricep kickbacks (15 reps x 3 sets)
Hip thrusts (12 reps x 3 sets)
Seated rows (10 reps x 4 sets)
-------------------------------------------------------------------------------------

Bye Lucas.
Expand (47 lines)
Error handling
Your program should be able to handle input errors from the user. If there is an error, the program will continually ask for input until it is valid.

The program should only accept alphabetical characters from [a-z][A-Z] and spaces, when the user enters their name. Here is an example of the correct format:

Please enter your name: #Lucas
And here is an example of an error:

Please enter your name: #LuC1!
Error: Only accept alphabetical characters and spaces for name
The age is a number between [0-110]. An example of an error:

Please enter your age: #800
Error: The age is a number between 0 to 110
Sex is only "male" or "female" (case sensitive). An example of an error case:

Please enter your biological sex (female/male): #M
Error: Please enter valid input
In the above example goal is an option between 1 to 6. An example of an error case:

What do you want to get out of your training?
1. Your goal is losing weight
2. Your goal is to staying calm and relax
3. Your goal is increasing your heart rate
4. Your goal is having stronger legs
5. Your goal is having stronger ABS
6. Your goal is having stronger shoulders and arms
Choose a number between 1 to 6: #0
Error - It can only be a number between 1 to 6

And the last input is the number of training days, which can be a number between 1 to 7. An example of an error for this field:

How many days per week you can train: #8
Error: It can only be a number between 1 to 7
Here is an example of executing your program when there is an input error from the user:

$ python3 gym.py
Please enter your name: #Lucas

Please enter your age: #19

Please enter your biological sex (female/male): #male

What do you want to get out of your training?
1. Your goal is losing weight
2. Your goal is to staying calm and relax
3. Your goal is increasing your heart rate
4. Your goal is having stronger legs
5. Your goal is having stronger ABS
6. Your goal is having stronger shoulders and arms
Choose a number between 1 to 6: #60
Error - It can only be a number between 1 to 6

What do you want to get out of your training?
1. Your goal is losing weight
2. Your goal is to staying calm and relax
3. Your goal is increasing your heart rate
4. Your goal is having stronger legs
5. Your goal is having stronger ABS
6. Your goal is having stronger shoulders and arms
Choose a number between 1 to 6: #1

How many days per week you can train: 2

Hello Lucas! Here is your training:
-------------------------------------------------------------------------------------
Day 1
Gym workout for fat loss

Plate thrusters (15 reps x 3 sets)
Mountain climbers (20 reps x 3 sets)
Box jumps (10 reps x 3 sets)
Lounges (10 reps x 3 sets)
Renegade rows (10 reps x 3 sets)
Press ups (15 reps x 3 sets)
Treadmill (10 mins x 3 sets)
Supermans (10 reps x 3 sets)
Crunches (10 reps x 3 sets)
-------------------------------------------------------------------------------------
Day 2
Gym workout for a male at least 18 years old

Standing biceps curls (20 reps x 3 sets)
Seated incline curls (18 reps x 3 sets)
Seated dumbbell presses (12 reps x 3 sets)
Leg presses (15 reps x 3 sets)
Bench presses (10 reps x 4 sets)
Tricep kickbacks (15 reps x 3 sets)
Hip thrusts (12 reps x 3 sets)
Seated rows (10 reps x 4 sets)
-------------------------------------------------------------------------------------

Bye Lucas.
Expand (57 lines) Hints and Extra Information
You should always print an empty line directly before asking the user for input.

Inputs are case-sensitive. For example, female is valid, but Female is invalid.

Code Submission
Your code submission must be made via Ed in this lesson.

To make a submission, you will need to press the "Mark" button.

You may submit as many times as you wish without penalty.

You are able to view previous submissions from the code submission section.

Every submission you make should include the gym.py file

The following rules apply to your code submission:

Only the file gym.py will be graded by the automarker

Only the last submission will be graded.

Your submission must be able to compile and run within the Ed environment provided.

After each submission, the marking system will automatically check your code against the public test cases.

The Python version is that which is presently being used on the Ed system:

$ python3 --version
Python 3.10.5
Please ensure you carefully follow the assignment description. Your program output must exactly match the output shown in the examples.

Marking criteria
This part of the assignment is worth 5% of your final course grade.

The grade you will receive is based on the number of test cases passed.

We have provided you with some sample test cases but these do not test all the functionality described in the assignment. It is important that you check your own code to ensure its correctness.

Automatic previva tests 5 / 5
These are marked by a computer.

There are public test cases

There are hidden test cases

There are private test cases

Please include comments in your code. These will be used in the marking process.

The minimum requirement for the viva
To participate in the viva you need to pass at least three automatic test cases. This includes the example test case as shown above.

Late Submissions
No late submissions are permitted.

Please do not make any submissions after the deadline. Remember, we will be marking the last submission you make.


Friendly note
Sometimes we find typos or other errors in specifications. Sometimes the specification could be clearer. Students and tutors often make great suggestions for improving the specification. Therefore, this assignment specification may be clarified up to Week 4, Thursday, August 25th. No major changes will be made. Revised versions will be clearly marked and the most recent version will be available here.


Academic declaration
By submitting this assignment, you declare the following:

I declare that I have read and understood the University of Sydney Student Plagiarism: Coursework Policy and Procedure, and except where specifically acknowledged, the work contained in this assignment/project is my work and has not been copied from other sources been previously submitted for award or assessment.

I understand that failure to comply with the Student Plagiarism: Coursework Policy and Procedure can lead to severe penalties as outlined under Chapter 8 of the University of Sydney By-Law 1999 (as amended). These penalties may be imposed in cases where any significant portion of my submitted work has been copied without proper acknowledgment from other sources, including published works, the Internet, existing programs, the work of other students, or work previously submitted for other awards or assessments.

I realize that I may be asked to identify those portions of the work contributed by me and required to demonstrate my knowledge of the relevant material by answering oral questions or by undertaking supplementary work, either written or in the laboratory, in order to arrive at the final assessment mark.

I acknowledge that the School of Computer Science, in assessing this assignment, may reproduce it entirely, may provide a copy to another member of faculty, and/or communicate a copy of this assignment to a plagiarism checking service or in-house computer program, and that a copy of the assignment may be maintained by the service or the School of Computer Science for the purpose of future plagiarism checking.

Warning: Any attempts to deceive or disrupt the marking system will result in an immediate zero for the entire assignment. Negative marks can be assigned if you do not properly follow the assignment description, or your code is unnecessarily or deliberately obfuscated.

Contents of the readme.md file:

#These are ten categories of workouts you need to add to your program:

#1
Gym workout for fat loss

Plate thrusters (15 reps x 3 sets)
Mountain climbers (20 reps x 3 sets)
Box jumps (10 reps x 3 sets)
Lunges (10 reps x 3 sets)
Renegade rows (10 reps x 3 sets)
Press ups (15 reps x 3 sets)
Treadmill (10 mins x 3 sets)
Supermans (10 reps x 3 sets)
Crunches (10 reps x 3 sets)

#2------------------------------------------------------
Gym workout for stretch and relax

Quad stretchs (2 mins x 3 sets)
Hamstring stretchs (2 mins x 3 sets)
Chest and shoulder stretchs (2 mins x 2 sets)
Upper back stretchs (3 mins x 2 sets)
Biceps stretchs (2 mins x 2 sets)
Triceps stretchs (2 mins x 3 sets)
Hip flexors (2 mins x 3 sets)
Calf stretchs (2 mins x 3 sets)
Lower back stretchs (2 mins x 3 sets)

#3------------------------------------------------------
Gym workout for high-intensity exercises

Jumping jacks (20 reps x 4 sets)
Sprints (20 reps x 3 sets)
Mountain climbers (20 reps x 4 sets)
Squat jumps (20 reps x 4 sets)
Lunges (20 reps x 3 sets)
Crunches (20 reps x 3 sets)
Treadmill (15 mins x 2 sets)
Side planks (15 reps x 3 sets)
Burpees (15 reps x 3 sets)

#4------------------------------------------------------
Gym workout for strong legs

Back squats (10 reps x 5 sets)
Hip thrusts (12 reps x 3 sets)
Overhead presses (10 reps x 5 sets)
Rack pulls (10 reps x 5 sets)
Squats (10 reps x 4 sets)
Dumbbell lunges (10 reps x 3 sets)
Leg curls (15 reps x 3 sets)
Standing calf raises (20 reps x 2 sets)

#5------------------------------------------------------
Gym workout for strong ABS

Cross crunchs (12 reps x 3 sets)
Knee ups (15 reps x 5 sets)
Hip thrusts (15 reps x 3 sets)
Mountain climbers (15 reps x 3 sets)
Vertical hip thrusts (12 reps x 3 sets)
Bicycles (15 mins x 2 sets)
Front planks (15 mins x 3 sets)
Dragon flags (12 reps x 4 sets)
Reverse crunches (10 reps x 3 sets)

#6------------------------------------------------------
Gym workout for strong shoulder and arms

Bench presses (10 reps x 5 sets)
Triceps dips (10 reps x 5 sets)
Incline dumbbell presses (12 reps x 3 sets)
dumbbell flyes (15 reps x 3 sets)
Triceps extensions (15 reps x 3 sets)
Pull ups (10 reps x 5 sets)
Treadmill (15 mins x 2 sets)
Bent over rows (10 reps x 5 sets)
Chin ups (10 reps x 3 sets)

#7------------------------------------------------------
Gym workout for a male younger than 18 years old

High knees (20 reps x 3 sets)
Squats (10 reps x 3 sets)
Calf raises (10 reps x 3 sets)
Scissor jumps (12 reps x 3 sets)
Burpees (10 reps x 3 sets)
Treadmill (10 mins x 2 sets)

#8------------------------------------------------------
Gym workout for a female younger than 18 years old

Squats (10 reps x 3 sets)
Crunches (10 reps x 2 sets)
Jumping jacks (10 reps x 3 sets)
Push ups (10 reps x 2 sets)
Burpees (10 reps x 3 sets)
Treadmill (10 mins x 2 sets)

#9------------------------------------------------------
Gym workout for a male at least 18 years old

Standing biceps curls (20 reps x 3 sets)
Seated incline curls (18 reps x 3 sets)
Seated dumbbell presses (12 reps x 3 sets)
Leg presses (15 reps x 3 sets)
Bench presses (10 reps x 4 sets)
Tricep kickbacks (15 reps x 3 sets)
Hip thrusts (12 reps x 3 sets)
Seated rows (10 reps x 4 sets)

#10------------------------------------------------------
Gym workout for a female at least 18 years old

Lateral raises (15 reps x 3 sets)
Reverse flyes (12 reps x 3 sets)
Hip thrusts (12 reps x 3 sets)
Incline dumbbell presses (15 reps x 3 sets)
Squats (10 reps x 4 sets)
Dumbbell lunges (10 reps x 3 sets)
Leg presses (12 reps x 3 sets)
Dumbbell presses (10 reps x 4 sets)

#------------------------------------------------------