Sharks in Australia
Project 2
Jiayu Sun 510098700
University of Sydney | Math 1005 | 05/28
1 Executive Summary
The goal of this report is to study sharks caught in Queensland, ask questions and make assumptions based on factors such as temperature, geographic location, and time, and then solve the problem. I asked two questions based on the above information. 1.Which area has the most sharks caught and why? 2. Does temperature affect sharks length? Does temperature affect the length of sharks? I made a hypothesis for the second question, assuming that temperature doesn’t affect the length of the sharks. In addition, the main discovery is that tiger sharks are the most species has been caught and they were the relatively large group of sharks.
2 Initial Data Analysis (IDA)
library(readr)
sharks_updated_1 <- read_csv("C:/Users/Crycry/Desktop/Math 1005/sharks_updated-1.csv")##
## -- Column specification --------------------------------------------------------
## cols(
## `Species Name` = col_character(),
## Area = col_character(),
## Location = col_character(),
## `Length (m)` = col_double(),
## `Water Temp (C)` = col_double(),
## Month = col_character()
## )Data1 <- sharks_updated_1
# Quick look at top 6 rows of Data1
head(sharks_updated_1)## # A tibble: 6 x 6
## `Species Name` Area Location `Length (m)` `Water Temp (C)` Month
## <chr> <chr> <chr> <dbl> <dbl> <chr>
## 1 AUSTRALIAN BLACKT~ Cairns Holloways Beach 1 27 Novem~
## 2 BLACKTIP REEF WHA~ Cairns Buchans Point ~ 0.7 27 Janua~
## 3 BLACKTIP REEF WHA~ Cairns Ellis Beach 1.5 27 Janua~
## 4 BLACKTIP REEF WHA~ Mackay Harbour Beach 2.2 26 Janua~
## 5 BLACKTIP REEF WHA~ Mackay Harbour Beach 1.7 26 Janua~
## 6 BLACKTIP REEF WHA~ Cairns Holloways Beach 1.2 29 Janua~## Size of Data1
dim(sharks_updated_1)## [1] 532 6## R's classification of Data1
class(sharks_updated_1)## [1] "spec_tbl_df" "tbl_df" "tbl" "data.frame"## R's classification of variables for Data1
str(sharks_updated_1)## spec_tbl_df [532 x 6] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ Species Name : chr [1:532] "AUSTRALIAN BLACKTIP" "BLACKTIP REEF WHALER" "BLACKTIP REEF WHALER" "BLACKTIP REEF WHALER" ...
## $ Area : chr [1:532] "Cairns" "Cairns" "Cairns" "Mackay" ...
## $ Location : chr [1:532] "Holloways Beach" "Buchans Point Beach" "Ellis Beach" "Harbour Beach" ...
## $ Length (m) : num [1:532] 1 0.7 1.5 2.2 1.7 1.2 0.75 1.2 0.8 1.3 ...
## $ Water Temp (C): num [1:532] 27 27 27 26 26 29 30 31 29 29 ...
## $ Month : chr [1:532] "November" "January" "January" "January" ...
## - attr(*, "spec")=
## .. cols(
## .. `Species Name` = col_character(),
## .. Area = col_character(),
## .. Location = col_character(),
## .. `Length (m)` = col_double(),
## .. `Water Temp (C)` = col_double(),
## .. Month = col_character()
## .. )2.1 IDA complexity
The data contained 10 variables which all displayed the related data of sharks. Nevertheless, the variable of the days of weeks, and the date of the sharks were repeated, and latitude and longtitude were less related with two research questions that I decided to do the investigation. Therefore, we changed to 6 variables to be used in Rstudio. These variables included the name of sharks, area, location, latitude, longitude, length, and temperature. The raw dataset was disorganized since the types of sharks were too many. Thus, to make the dataset systematic, simplify all types of sharks to individual groups by using RStudio.
2.2 IDA classification
6 variables were used in this project, i.e. name of sharks, the latitude of shark habitat, length, area, month and temperature of sharks’ living environment. Other variables belong to qualitative data, they were repeated and less associated with this report, thus, directly deleted in the raw dataset. This situation would cause the raw dataset only quantitative data left. Furthermore, the raw dataset is sorted according to the species of sharks, and in alphabetical order. Nevertheless, this order is inappropriate with the research that I wanted to analyze. To clarify the dataset which satisfies these research question, based on the shark species, they are divided into different groups(omitted shark species less than ten) to compare the length and temperature and calculate the average value, so that they can be compared with other shark species.
3 Domain knowledge
Queensland’s beaches are great places to swim and surf, but be aware that sharks inhabit our coastline, as well as estuaries, rivers, creeks, canals, and streams. The Shark Control Program aims to reduce the risk of shark bites in Queensland coastal waters. To ensure the safety of humans the government set five policies. 1. To allocate $250000 to conduct scientific research on the prevalence and behavior of sharks in the seaports of West Germany. 2. Keep West Germany port as a no swimming zone until the completion of scientific research. The West German port is still a no swimming zone. There are signs around the West German port and nearby docks to advise people not to swim. 3. Carry out an eye-catching education activity to educate local people and tourists on shark safety immediately. 4. Launch a broader shark smart education campaign, similar to the successful cruise campaign in northern Queensland. 5. Continue to meet with industry stakeholders and experts to develop and promote response measures. (https://www.daf.qld.gov.au/business-priorities/fisheries/shark-control-program/whitsundays-plan, 2020)
4 Research Question 1
Data1 <- read.csv("C:/Users/Crycry/Desktop/Math 1005/sharks_updated-1.csv")
area <- Data1$Area
par(mar= c(6,4,4,1))
barplot(table(area), main="different area that sharks be caught",cex.main=1, cex.lab=0.7, cex.axis= 0.7, col="mistyrose3", las=2)
#x-axis
mtext(text="area",
side=1,line=10)
#y-axis
mtext(text="the number of sharks",
side=2,#side 2= left
line=3.2)
temperature <- Data1$Water.Temp..C.
par(mar= c(6,4,4,1))
barplot(table(temperature), main="different temperature that tiger sharks live in",cex.main=1, cex.lab=0.7, cex.axis= 0.7, col="mistyrose3", las=2)
#x-axis
mtext(text="temperature",
side=1,line=10)
#y-axis
mtext(text="the number of sharks",
side=2,#side 2= left
line=3.2)
length <- Data1$Length..m.
temperature <- Data1$Water.Temp..C.
scatter.smooth(temperature,length,xlab="temperature",ylab="length", main="the raltionship between temperature and length",cex.main=0.7,cex.lab=0.7,cex.axis=0.7)
The area that could catch the most of the sharks is Townsville. Since the sharks usually hunt in warm temperature, and usually around 19-25˚C. This information is demonstrated by the graph related to the temperature in question 1 coding part. Thus, I think this result(area) should be related to the temperature and location. Due to the weird location, the winter rainfall in Townsville is not as high as in other parts of the tropical east coast of Queensland. In winter, the weather is mostly sunny with the southeast wind. On the coastline further north, it stretches from north to south, and there is continuous commercial wind to produce rainfall throughout the year. However, Townsville is located on the east/west turn of the coastline, so there is no lifting effect. So, although there may be a lot of rain sometimes, winter is mainly blue sky, warm days, and cool nights(https://en.wikipedia.org/wiki/Townsville#Urban_layout, 2017). Therefore, the temperature at Townsville is usually around 23˚C, sharks are active in this temperature, and are appropriate in this living habitat.
5 Research Question 2
species <- Data1$Species.Name
par(mar= c(13,4,4,1))
barplot(table(species), main="Frequency of different types of sharks that be caught",cex.main=1, cex.lab=0.7, cex.axis= 0.7, col="mistyrose3", las=2)
#x-axis
mtext(text="species",
side=1,line=10)
#y-axis
mtext(text="the number be caught",
side=2,#side 2= left
line=3.2)
month <- Data1$Month
par(mar= c(6,4,4,1))
barplot(table(month), main="different month that sharks be caught",cex.main=1, cex.lab=0.7, cex.axis= 0.7, col="mistyrose3", las=2)
#x-axis
mtext(text="month",
side=1,line=10)
#y-axis
mtext(text="the number of sharks",
side=2,#side 2= left
line=3.2)
Data1[c(2:21),c(1,2,4,5)]## Species.Name Area Length..m. Water.Temp..C.
## 2 BLACKTIP REEF WHALER Cairns 0.70 27
## 3 BLACKTIP REEF WHALER Cairns 1.50 27
## 4 BLACKTIP REEF WHALER Mackay 2.20 26
## 5 BLACKTIP REEF WHALER Mackay 1.70 26
## 6 BLACKTIP REEF WHALER Cairns 1.20 29
## 7 BLACKTIP REEF WHALER Cairns 0.75 30
## 8 BLACKTIP REEF WHALER Townsville 1.20 31
## 9 BLACKTIP REEF WHALER Cairns 0.80 29
## 10 BLACKTIP REEF WHALER Cairns 1.30 29
## 11 BLACKTIP REEF WHALER Cairns 1.60 27
## 12 BLACKTIP REEF WHALER Capricorn Coast 1.05 25
## 13 BLACKTIP REEF WHALER Townsville 1.22 23
## 14 BLACKTIP REEF WHALER Cairns 0.80 25
## 15 BLACKTIP REEF WHALER Cairns 1.20 25
## 16 BLACKTIP REEF WHALER Townsville 1.10 24
## 17 BLACKTIP REEF WHALER Townsville 1.13 23
## 18 BLACKTIP REEF WHALER Townsville 1.25 27
## 19 BLACKTIP REEF WHALER Cairns 0.85 26
## 20 BLACKTIP REEF WHALER Mackay 1.80 25
## 21 BLACKTIP REEF WHALER Gladstone 0.90 27Data2=Data1[c(2:21),c(1,2,4,5)]
Data3=Data1[c(22:112),c(1,2,4,5)]
Data4=Data1[c(113:151),c(1,2,4,5)]
Data5=Data1[c(158:179),c(1,2,4,5)]
Data6=Data1[c(187:222),c(1,2,4,5)]
Data7=Data1[c(231:244),c(1,2,4,5)]
Data8=Data1[c(250:265),c(1,2,4,5)]
Data9=Data1[c(272:293),c(1,2,4,5)]
Data10=Data1[c(294:316),c(1,2,4,5)]
Data11=Data1[c(317:523),c(1,2,4,5)]
Data1[c(317:523), c(1,2,4,5)]## Species.Name Area Length..m. Water.Temp..C.
## 317 TIGER SHARK Capricorn Coast 1.51 27
## 318 TIGER SHARK Gladstone 2.75 26
## 319 TIGER SHARK Bundaberg 1.97 25
## 320 TIGER SHARK Cairns 1.20 29
## 321 TIGER SHARK Cairns 1.00 29
## 322 TIGER SHARK Cairns 3.90 29
## 323 TIGER SHARK Nth Stradbroke Is. 1.10 27
## 324 TIGER SHARK Cairns 3.40 29
## 325 TIGER SHARK Mackay 1.90 26
## 326 TIGER SHARK Rainbow Beach 2.60 26
## 327 TIGER SHARK Gladstone 3.85 27
## 328 TIGER SHARK Mackay 1.60 26
## 329 TIGER SHARK Townsville 1.85 30
## 330 TIGER SHARK Mackay 1.40 26
## 331 TIGER SHARK Mackay 3.20 27
## 332 TIGER SHARK Townsville 3.50 30
## 333 TIGER SHARK Mackay 2.40 27
## 334 TIGER SHARK Mackay 2.50 27
## 335 TIGER SHARK Townsville 3.80 31
## 336 TIGER SHARK Gold Coast 2.31 25
## 337 TIGER SHARK Townsville 3.70 31
## 338 TIGER SHARK Townsville 1.80 31
## 339 TIGER SHARK Capricorn Coast 2.10 27
## 340 TIGER SHARK Bundaberg 3.12 27
## 341 TIGER SHARK Gold Coast 3.15 26
## 342 TIGER SHARK Rainbow Beach 2.35 25
## 343 TIGER SHARK Townsville 2.25 31
## 344 TIGER SHARK Mackay 2.40 27
## 345 TIGER SHARK Capricorn Coast 3.80 27
## 346 TIGER SHARK Rainbow Beach 1.85 25
## 347 TIGER SHARK Rainbow Beach 3.30 25
## 348 TIGER SHARK Mackay 2.10 27
## 349 TIGER SHARK Townsville 1.70 30
## 350 TIGER SHARK Bundaberg 3.50 26
## 351 TIGER SHARK Townsville 1.40 30
## 352 TIGER SHARK Townsville 1.35 30
## 353 TIGER SHARK Townsville 2.10 30
## 354 TIGER SHARK Gold Coast 3.65 27
## 355 TIGER SHARK Sunshine Coast North 0.90 24
## 356 TIGER SHARK Cairns 1.80 29
## 357 TIGER SHARK Bundaberg 2.50 26
## 358 TIGER SHARK Mackay 2.30 27
## 359 TIGER SHARK Cairns 3.10 29
## 360 TIGER SHARK Mackay 2.20 27
## 361 TIGER SHARK Mackay 3.40 27
## 362 TIGER SHARK Mackay 2.10 27
## 363 TIGER SHARK Rainbow Beach 1.40 27
## 364 TIGER SHARK Bundaberg 3.57 25
## 365 TIGER SHARK Bundaberg 3.08 25
## 366 TIGER SHARK Rainbow Beach 1.40 27
## 367 TIGER SHARK Bundaberg 2.00 25
## 368 TIGER SHARK Rainbow Beach 3.95 27
## 369 TIGER SHARK Mackay 2.80 27
## 370 TIGER SHARK Townsville 1.40 29
## 371 TIGER SHARK Cairns 2.20 29
## 372 TIGER SHARK Townsville 1.85 29
## 373 TIGER SHARK Townsville 3.70 29
## 374 TIGER SHARK Mackay 2.00 27
## 375 TIGER SHARK Mackay 2.60 26
## 376 TIGER SHARK Mackay 3.40 26
## 377 TIGER SHARK Cairns 0.70 29
## 378 TIGER SHARK Cairns 1.70 27
## 379 TIGER SHARK Townsville 2.00 28
## 380 TIGER SHARK Gladstone 3.35 27
## 381 TIGER SHARK Cairns 2.90 27
## 382 TIGER SHARK Gladstone 2.60 26
## 383 TIGER SHARK Gladstone 3.70 26
## 384 TIGER SHARK Townsville 1.50 29
## 385 TIGER SHARK Townsville 3.50 29
## 386 TIGER SHARK Townsville 3.60 27
## 387 TIGER SHARK Mackay 2.10 26
## 388 TIGER SHARK Bundaberg 1.60 23
## 389 TIGER SHARK Rainbow Beach 2.30 25
## 390 TIGER SHARK Bundaberg 2.70 23
## 391 TIGER SHARK Mackay 1.70 26
## 392 TIGER SHARK Mackay 2.00 25
## 393 TIGER SHARK Sunshine Coast South & Bribie Island 1.00 24
## 394 TIGER SHARK Mackay 1.80 25
## 395 TIGER SHARK Mackay 2.00 25
## 396 TIGER SHARK Mackay 2.00 25
## 397 TIGER SHARK Bundaberg 3.16 24
## 398 TIGER SHARK Bundaberg 2.70 24
## 399 TIGER SHARK Mackay 3.80 25
## 400 TIGER SHARK Mackay 2.40 25
## 401 TIGER SHARK Cairns 1.40 27
## 402 TIGER SHARK Bundaberg 3.37 23
## 403 TIGER SHARK Rainbow Beach 1.70 24
## 404 TIGER SHARK Bundaberg 2.03 23
## 405 TIGER SHARK Capricorn Coast 3.12 25
## 406 TIGER SHARK Townsville 2.45 26
## 407 TIGER SHARK Cairns 2.10 25
## 408 TIGER SHARK Cairns 2.10 25
## 409 TIGER SHARK Townsville 3.65 26
## 410 TIGER SHARK Bundaberg 1.13 23
## 411 TIGER SHARK Bundaberg 2.15 22
## 412 TIGER SHARK Sunshine Coast North 2.01 23
## 413 TIGER SHARK Sunshine Coast North 1.02 23
## 414 TIGER SHARK Townsville 1.30 26
## 415 TIGER SHARK Bundaberg 4.09 22
## 416 TIGER SHARK Mackay 3.00 25
## 417 TIGER SHARK Mackay 2.40 25
## 418 TIGER SHARK Mackay 2.50 25
## 419 TIGER SHARK Townsville 1.30 26
## 420 TIGER SHARK Gladstone 1.60 24
## 421 TIGER SHARK Gold Coast 1.78 23
## 422 TIGER SHARK Townsville 0.89 25
## 423 TIGER SHARK Mackay 2.00 25
## 424 TIGER SHARK Townsville 1.05 25
## 425 TIGER SHARK Townsville 2.00 25
## 426 TIGER SHARK Bundaberg 1.95 21
## 427 TIGER SHARK Townsville 3.80 24
## 428 TIGER SHARK Townsville 3.10 24
## 429 TIGER SHARK Cairns 4.10 25
## 430 TIGER SHARK Rainbow Beach 2.90 21
## 431 TIGER SHARK Mackay 1.90 24
## 432 TIGER SHARK Capricorn Coast 2.08 21
## 433 TIGER SHARK Mackay 2.40 24
## 434 TIGER SHARK Bundaberg 1.48 18
## 435 TIGER SHARK Rainbow Beach 2.35 20
## 436 TIGER SHARK Townsville 4.00 22
## 437 TIGER SHARK Townsville 1.95 22
## 438 TIGER SHARK Cairns 2.70 23
## 439 TIGER SHARK Mackay 2.01 24
## 440 TIGER SHARK Bundaberg 1.41 17
## 441 TIGER SHARK Mackay 3.60 24
## 442 TIGER SHARK Townsville 3.20 24
## 443 TIGER SHARK Bundaberg 2.32 17
## 444 TIGER SHARK Mackay 2.40 24
## 445 TIGER SHARK Rainbow Beach 2.60 21
## 446 TIGER SHARK Bundaberg 1.95 17
## 447 TIGER SHARK Mackay 2.30 24
## 448 TIGER SHARK Rainbow Beach 3.85 20
## 449 TIGER SHARK Cairns 1.40 23
## 450 TIGER SHARK Cairns 2.40 23
## 451 TIGER SHARK Cairns 1.24 22
## 452 TIGER SHARK Mackay 2.20 24
## 453 TIGER SHARK Bundaberg 1.28 17
## 454 TIGER SHARK Mackay 3.20 24
## 455 TIGER SHARK Townsville 2.50 23
## 456 TIGER SHARK Bundaberg 2.37 17
## 457 TIGER SHARK Townsville 2.35 23
## 458 TIGER SHARK Townsville 2.00 23
## 459 TIGER SHARK Cairns 2.60 22
## 460 TIGER SHARK Townsville 1.13 23
## 461 TIGER SHARK Gold Coast 3.50 20
## 462 TIGER SHARK Bundaberg 1.56 19
## 463 TIGER SHARK Bundaberg 2.26 19
## 464 TIGER SHARK Townsville 2.30 24
## 465 TIGER SHARK Mackay 3.40 24
## 466 TIGER SHARK Mackay 2.80 24
## 467 TIGER SHARK Bundaberg 3.20 20
## 468 TIGER SHARK Nth Stradbroke Is. 3.50 21
## 469 TIGER SHARK Mackay 2.80 23
## 470 TIGER SHARK Mackay 3.20 23
## 471 TIGER SHARK Mackay 2.70 23
## 472 TIGER SHARK Townsville 1.40 26
## 473 TIGER SHARK Nth Stradbroke Is. 3.90 21
## 474 TIGER SHARK Rainbow Beach 3.65 22
## 475 TIGER SHARK Townsville 3.55 27
## 476 TIGER SHARK Bundaberg 1.42 21
## 477 TIGER SHARK Mackay 2.20 23
## 478 TIGER SHARK Sunshine Coast North 2.85 20
## 479 TIGER SHARK Sunshine Coast North 3.21 23
## 480 TIGER SHARK Sunshine Coast North 2.51 23
## 481 TIGER SHARK Bundaberg 2.76 21
## 482 TIGER SHARK Capricorn Coast 3.65 23
## 483 TIGER SHARK Gold Coast 3.04 18
## 484 TIGER SHARK Capricorn Coast 3.65 23
## 485 TIGER SHARK Gold Coast 3.04 18
## 486 TIGER SHARK Nth Stradbroke Is. 2.80 20
## 487 TIGER SHARK Rainbow Beach 2.75 22
## 488 TIGER SHARK Sunshine Coast North 2.54 21
## 489 TIGER SHARK Sunshine Coast North 3.34 21
## 490 TIGER SHARK Townsville 3.50 26
## 491 TIGER SHARK Capricorn Coast 3.46 23
## 492 TIGER SHARK Nth Stradbroke Is. 3.10 21
## 493 TIGER SHARK Mackay 2.00 24
## 494 TIGER SHARK Mackay 2.20 24
## 495 TIGER SHARK Rainbow Beach 3.15 22
## 496 TIGER SHARK Mackay 2.10 25
## 497 TIGER SHARK Sunshine Coast North 3.76 23
## 498 TIGER SHARK Cairns 3.10 26
## 499 TIGER SHARK Mackay 2.30 25
## 500 TIGER SHARK Sunshine Coast North 2.45 23
## 501 TIGER SHARK Nth Stradbroke Is. 3.00 22
## 502 TIGER SHARK Townsville 1.40 28
## 503 TIGER SHARK Townsville 2.15 28
## 504 TIGER SHARK Mackay 2.20 25
## 505 TIGER SHARK Mackay 2.30 25
## 506 TIGER SHARK Mackay 1.60 25
## 507 TIGER SHARK Bundaberg 2.10 24
## 508 TIGER SHARK Bundaberg 2.73 24
## 509 TIGER SHARK Townsville 2.55 28
## 510 TIGER SHARK Mackay 2.00 25
## 511 TIGER SHARK Townsville 3.00 28
## 512 TIGER SHARK Townsville 1.70 28
## 513 TIGER SHARK Bundaberg 3.28 25
## 514 TIGER SHARK Cairns 2.30 29
## 515 TIGER SHARK Bundaberg 1.82 25
## 516 TIGER SHARK Rainbow Beach 2.47 25
## 517 TIGER SHARK Townsville 3.10 29
## 518 TIGER SHARK Cairns 0.88 28
## 519 TIGER SHARK Mackay 2.00 27
## 520 TIGER SHARK Gold Coast 2.50 24
## 521 TIGER SHARK Townsville 1.95 30
## 522 TIGER SHARK Townsville 3.00 30
## 523 TIGER SHARK Townsville 3.50 31Data11=Data1[c(317:523),c(1,2,4,5)]
length <- Data11$Length..m.
par(mar= c(6,4,4,1))
barplot(table(length), main = "different length of tiger sharks",cex.main=1, cex.lab=0.7, cex.axis= 0.7, col="mistyrose3", las=2)
#x-axis
mtext(text="length",
side=1,line=8)
#y-axis
mtext(text="the number of sharks",
side=2,#side 2= left
line=3.2)
temperature <- Data11$Water.Temp..C.
par(mar= c(6,4,4,1))
barplot(table(temperature), main="different temperature that tiger sharks live in",cex.main=1, cex.lab=0.7, cex.axis= 0.7, col="mistyrose3", las=2)
#x-axis
mtext(text="temperature",
side=1,line=10)
#y-axis
mtext(text="the number of sharks",
side=2,#side 2= left
line=3.2)
scatter.smooth(length,temperature)
t.test(temperature,length,mu=0, alt="two.sided", var.eq= TRUE, paired= TRUE)##
## Paired t-test
##
## data: temperature and length
## t = 101.47, df = 206, p-value < 2.2e-16
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 21.97941 22.85044
## sample estimates:
## mean of the differences
## 22.41493From the coding I did in RStudio, I sorted the raw data, made separate and distinct tables for each type of shark, and analyzed them. Then, the variables of each table were compared, which led to the conclusion that the number of tiger sharks caught was the highest. The tiger shark, Galeocerdo cuvier, is a highly competent predator in a variety of nearshore ecosystems around the world. Compared to other large sharks, tiger sharks are the most common species accounting for 94% of the species. The TL range of tiger sharks is 148-407 cm. The overall sex ratio is skewed towards females at 1.8:1, but the sex ratio of adults is roughly 1:1 without much difference. Tiger sharks were caught more frequently during the day than at night in all habitats, and the catch rate of tiger sharks was highly correlated with water temperature, with the highest catch rates occurring when water temperatures were above 19°C(Michael R. Heithaus, 2001). I came to the following two conclusions from the above information. Initially, tiger sharks feed more when the temperature is higher, so in February, tiger sharks will become exceptionally active because of frequent feeding. This behavior will attract the attention of the shark hunting team and thus be hunted. Furthermore, the number of tiger sharks is much higher than other species of sharks, so they are more likely to be found and caught. In addition, from the result of t-test that “alternative hypothesis: true difference in means is not equal to 0”, I understand that length will be influenced by temperature.
6 References (if needed)
Bureau of Meteorology. Archived from the original on 5 October 2017. Retrieved from https://en.wikipedia.org/wiki/Townsville#Urban_layout
Michael R. Heithaus (2001) The Biology of Tiger Sharks, Galeocerdo Cuvier, in Shark Bay, Western Australia: Sex Ratio, Size Distribution, Diet, and Seasonal Changes in Catch Rates Environmental Biology of Fishes volume 61, pages25–36. Retrieved from https://link.springer.com/article/10.1023/A:1011021210685
Queensland government Department of Agriculture and Fisheries(2020) Five-point response plan https://www.daf.qld.gov.au/business-priorities/fisheries/shark-control-program/whitsundays-plan