D and E pl 4. Use the data provided in Table 1 to answer questions 4(a)–4(e):Table 1. Seaweed (Ulva) biomass for a reef flat in the Philippines[quadrat size 0.25 m?; Hoisaeter and Matthiesen (1979)].Stratum Biomass (g)StratumArea (m?) Sample SizeМean (g)Variance (s)I21759.0.58890.1661II39961419.3857179.1121III159072.14293.7962IV10396.0.20000.1120(a) First, calculate strata weights based on the size (area) of each stratum(b) Calculate the stratified mean for Ulva biomass per quadrat. How does this compare to themean if the authors had used a simple random sampling (SRS) design? [hint: ỹSRSwhereand ỹ; are the sample size and stratum mean, respectively, for the ith stratum](c) Now calculate the standard error for the stratified mean (note: you can ignore the finitepopulation correction factor since the area sampled is less than 5%: area sampled =100*35*0.25 m²/8800 m² = 0.1%). (c) Now calculate the standard error for the stratified mean (note: you can ignore the finitepopulation correction factor since the area sampled is less than 5%: area sampled =100*35*0.25 m²/8800 m² = 0.1%).%3DStratified sampling provides gains in precision when strata are relatively homogeneous; i.e.the majority of the population variance is partitioned into the between-strata variance. Howdoes the between-strata variance (s) compare to the within-strata variance (s) in thisexample? Based on this comparison, how effective is the stratification? [use the followingformulas: si = E{w;(i - Yst)? and s, = Ew;s ; where w; is the weight for stratum iand ỹst is the stratified mean](d) The mean biomass per quadrat is not a very meaningful number. Estimate the total biomass(g) of Ulva for the entire reef flat and the standard error for the total biomass. [hint: totalnumber of possible quadrats = total area / quadrat size]%3D(e) Another more meaningful number would be the mean density of Ulva: estimate the meandensity (g m2) of Ulva and the standard error for the estimated density.

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